Habitable 3D Learning Environments for Situated Learning. - William H. Bares; Luke S. Zettlemoyer; James C. Lester (Intelligent Tutoring Systems, 1998)

Task-sensitive Cinematography Interfaces for Interactive 3D Learning Environments. - William H. Bares; Luke S. Zettlemoyer; Dennis W. Rodriguez; James C. Lester (IUI, 1998)

Explanatory Lifelike Evatars: Performing User-Centered Tasks in 3D Learning Environments. - James C. Lester; Luke S. Zettlemoyer; Joël P. Grégoire; William H. Bares (Agents, 1999)

A Visual Medium for Programmatic Control of Interactive Applications. - Luke S. Zettlemoyer; Robert St. Amant (CHI, 1999)

An Imprecise Mouse Gesture for the Fast Activation of Controls. - Martin S. Dulberg; Robert St. Amant; Luke S. Zettlemoyer (INTERACT, 1999)

IBOTS: Agent Control Through the User Interface. - Luke S. Zettlemoyer; Robert St. Amant; Martin S. Dulberg (IUI, 1999)

User Interface Softbots. - Robert St. Amant; Luke S. Zettlemoyer (AAAI/IAAI, 2000)

The user interface as an agent environment. - Robert St. Amant; Luke S. Zettlemoyer (Agents, 2000)

Visual Generalization in Programming by Example. - Robert St. Amant; Henry Lieberman; Richard Potter; Luke Zettlemoyer (Commun. ACM, 2000)

Visual Generalization in Programming by Example. - Robert St. Amant; Henry Lieberman; Richard Potter; Luke Zettlemoyer (Your Wish is My Command, 2001)

Learning Probabilistic Relational Planning Rules. - Hanna Pasula; Luke S. Zettlemoyer; Leslie Pack Kaelbling (KR, 2004)

Learning Planning Rules in Noisy Stochastic Worlds. - Luke S. Zettlemoyer; Hanna Pasula; Leslie Pack Kaelbling (AAAI, 2005)

Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars. - Luke S. Zettlemoyer; Michael Collins 001 (UAI, 2005)

Logical Particle Filtering. - Luke S. Zettlemoyer; Hanna M. Pasula; Leslie Pack Kaelbling (Probabilistic, Logical and Relational Learning - A Further Synthesis, 2007)

Online Learning of Relaxed CCG Grammars for Parsing to Logical Form. - Luke Zettlemoyer; Michael Collins 001 (EMNLP-CoNLL, 2007)

Selective Phrase Pair Extraction for Improved Statistical Machine Translation. - Luke Zettlemoyer; Robert Moore (HLT-NAACL (Short Papers), 2007)

Learning Probabilistic Relational Dynamics for Multiple Tasks. - Ashwin Deshpande; Brian Milch; Luke S. Zettlemoyer; Leslie Pack Kaelbling (UAI, 2007)

Learning Symbolic Models of Stochastic Domains. - Hanna M. Pasula; Luke S. Zettlemoyer; Leslie Pack Kaelbling (J. Artif. Intell. Res., 2007)

Lifted Probabilistic Inference with Counting Formulas. - Brian Milch; Luke S. Zettlemoyer; Kristian Kersting; Michael Haimes; Leslie Pack Kaelbling (AAAI, 2008)

A Generative Model for Parsing Natural Language to Meaning Representations. - Wei Lu 011; Hwee Tou Ng; Wee Sun Lee; Luke S. Zettlemoyer (EMNLP, 2008)

Multi-Agent Filtering with Infinitely Nested Beliefs. - Luke S. Zettlemoyer; Brian Milch; Leslie Pack Kaelbling (NIPS, 2008)

Reinforcement Learning for Mapping Instructions to Actions. - S. R. K. Branavan; Harr Chen; Luke Zettlemoyer; Regina Barzilay (ACL/IJCNLP, 2009)

Learning Context-Dependent Mappings from Sentences to Logical Form. - Luke Zettlemoyer; Michael Collins 001 (ACL/IJCNLP, 2009)

Learning to map sentences to logical form. - Luke S. Zettlemoyer (2009)

Reading between the Lines: Learning to Map High-Level Instructions to Commands. - S. R. K. Branavan; Luke Zettlemoyer; Regina Barzilay (ACL, 2010)

Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification. - Tom Kwiatkowski; Luke Zettlemoyer; Sharon Goldwater; Mark Steedman (EMNLP, 2010)

Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations. - Raphael Hoffmann; Congle Zhang; Xiao Ling; Luke Zettlemoyer; Daniel S. Weld (ACL, 2011)

Bootstrapping Semantic Parsers from Conversations. - Yoav Artzi; Luke Zettlemoyer (EMNLP, 2011)

Lexical Generalization in CCG Grammar Induction for Semantic Parsing. - Tom Kwiatkowski; Luke Zettlemoyer; Sharon Goldwater; Mark Steedman (EMNLP, 2011)

Discriminative Learning for Joint Template Filling. - Einat Minkov; Luke Zettlemoyer (ACL (1), 2012)

A Probabilistic Model of Syntactic and Semantic Acquisition from Child-Directed Utterances and their Meanings. - Tom Kwiatkowski; Sharon Goldwater; Luke Zettlemoyer; Mark Steedman (EACL, 2012)

A Joint Model of Language and Perception for Grounded Attribute Learning. - Cynthia Matuszek; Nicholas FitzGerald; Luke Zettlemoyer; Liefeng Bo; Dieter Fox (ICML, 2012)

Learning to Parse Natural Language Commands to a Robot Control System. - Cynthia Matuszek; Evan Herbst; Luke Zettlemoyer; Dieter Fox (ISER, 2012)

Using syntactic and confusion network structure for out-of-vocabulary word detection. - Alex Marin; Tom Kwiatkowski; Mari Ostendorf; Luke Zettlemoyer (SLT, 2012)

Learning STRIPS Operators from Noisy and Incomplete Observations. - Kira Mourão; Luke Zettlemoyer; Ronald P. A. Petrick; Mark Steedman (UAI, 2012)

RevMiner: an extractive interface for navigating reviews on a smartphone. - Jeff Huang 002; Oren Etzioni; Luke Zettlemoyer; Kevin Clark; Christian Lee (UIST, 2012)

Semantic Parsing with Combinatory Categorial Grammars. - Yoav Artzi; Nicholas FitzGerald; Luke Zettlemoyer (ACL (Tutorial Abstracts), 2013)

Paraphrase-Driven Learning for Open Question Answering. - Anthony Fader; Luke Zettlemoyer; Oren Etzioni (ACL (1), 2013)

Lightly Supervised Learning of Procedural Dialog Systems. - Svitlana Volkova; Pallavi Choudhury; Chris Quirk; Bill Dolan; Luke Zettlemoyer (ACL (1), 2013)

Learning Distributions over Logical Forms for Referring Expression Generation. - Nicholas FitzGerald; Yoav Artzi; Luke Zettlemoyer (EMNLP, 2013)

Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves. - Hannaneh Hajishirzi; Leila Zilles; Daniel S. Weld; Luke Zettlemoyer (EMNLP, 2013)

Scaling Semantic Parsers with On-the-Fly Ontology Matching. - Tom Kwiatkowski; Eunsol Choi; Yoav Artzi; Luke Zettlemoyer (EMNLP, 2013)

Automatic Idiom Identification in Wiktionary. - Grace Muzny; Luke Zettlemoyer (EMNLP, 2013)

"Can you give me another word for hyperbaric?": Improving speech translation using targeted clarification questions. - Necip Fazil Ayan; Arindam Mandal; Michael W. Frandsen; Jing Zheng 001; Peter Blasco; Andreas Kathol; Frédéric Béchet; Benoît Favre; Alex Marin; Tom Kwiatkowski; Mari Ostendorf; Luke Zettlemoyer; et al. (ICASSP, 2013)

Learning to Relate Literal and Sentimental Descriptions of Visual Properties. - Mark Yatskar; Svitlana Volkova; Asli Celikyilmaz; Bill Dolan; Luke Zettlemoyer (HLT-NAACL, 2013)

UW SPF: The University of Washington Semantic Parsing Framework. - Yoav Artzi; Luke Zettlemoyer (CoRR, 2013)

Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions. - Yoav Artzi; Luke Zettlemoyer (Trans. Assoc. Comput. Linguistics, 2013)

Modeling Missing Data in Distant Supervision for Information Extraction. - Alan Ritter; Luke Zettlemoyer; Mausam; Oren Etzioni (Trans. Assoc. Comput. Linguistics, 2013)

3D Wikipedia: using online text to automatically label and navigate reconstructed geometry. - Bryan C. Russell; Ricardo Martin-Brualla; Daniel J. Butler; Steven M. Seitz; Luke Zettlemoyer (ACM Trans. Graph., 2013)

Learning from Unscripted Deictic Gesture and Language for Human-Robot Interactions. - Cynthia Matuszek; Liefeng Bo; Luke Zettlemoyer; Dieter Fox (AAAI, 2014)

Learning to Automatically Solve Algebra Word Problems. - Nate Kushman; Luke Zettlemoyer; Regina Barzilay; Yoav Artzi (ACL (1), 2014)

Context-dependent Semantic Parsing for Time Expressions. - Kenton Lee; Yoav Artzi; Jesse Dodge; Luke Zettlemoyer (ACL (1), 2014)

Morpho-syntactic Lexical Generalization for CCG Semantic Parsing. - Adrienne X. Wang; Tom Kwiatkowski; Luke Zettlemoyer (EMNLP, 2014)

Open question answering over curated and extracted knowledge bases. - Anthony Fader; Luke Zettlemoyer; Oren Etzioni (KDD, 2014)

See No Evil, Say No Evil: Description Generation from Densely Labeled Images. - Mark Yatskar; Michel Galley; Lucy Vanderwende; Luke Zettlemoyer (*SEM@COLING, 2014)

Introduction to the special issue on learning semantics. - Antoine Bordes; Léon Bottou; Ronan Collobert; Dan Roth 001; Jason Weston; Luke Zettlemoyer (Mach. Learn., 2014)

Scalable Semantic Parsing with Partial Ontologies. - Eunsol Choi; Tom Kwiatkowski; Luke Zettlemoyer (ACL (1), 2015)

Broad-coverage CCG Semantic Parsing with AMR. - Yoav Artzi; Kenton Lee; Luke Zettlemoyer (EMNLP, 2015)

Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language. - Luheng He; Mike Lewis; Luke Zettlemoyer (EMNLP, 2015)

Mise en Place: Unsupervised Interpretation of Instructional Recipes. - Chloé Kiddon; Ganesa Thandavam Ponnuraj; Luke Zettlemoyer; Yejin Choi 001 (EMNLP, 2015)

Event Detection and Factuality Assessment with Non-Expert Supervision. - Kenton Lee; Yoav Artzi; Yejin Choi 001; Luke Zettlemoyer (EMNLP, 2015)

Joint A* CCG Parsing and Semantic Role Labelling. - Mike Lewis; Luheng He; Luke Zettlemoyer (EMNLP, 2015)

Robot Programming by Demonstration with situated spatial language understanding. - Maxwell Forbes; Rajesh P. N. Rao; Luke Zettlemoyer; Maya Cakmak (ICRA, 2015)

Personalized Mathematical Word Problem Generation. - Oleksandr Polozov; Eleanor O'Rourke; Adam M. Smith 001; Luke Zettlemoyer; Sumit Gulwani; Zoran Popovic (IJCAI, 2015)

Extreme Extraction: Only One Hour per Relation. - Raphael Hoffmann; Luke Zettlemoyer; Daniel S. Weld (CoRR, 2015)

Document-level Sentiment Inference with Social, Faction, and Discourse Context. - Eunsol Choi; Hannah Rashkin; Luke Zettlemoyer; Yejin Choi 001 (ACL (1), 2016)

Summarizing Source Code using a Neural Attention Model. - Srinivasan Iyer 001; Ioannis Konstas; Alvin Cheung; Luke Zettlemoyer (ACL (1), 2016)

Situation Recognition: Visual Semantic Role Labeling for Image Understanding. - Mark Yatskar; Luke Zettlemoyer; Ali Farhadi (CVPR, 2016)

Human-in-the-Loop Parsing. - Luheng He; Julian Michael; Mike Lewis; Luke Zettlemoyer (EMNLP, 2016)

Globally Coherent Text Generation with Neural Checklist Models. - Chloé Kiddon; Luke Zettlemoyer; Yejin Choi 001 (EMNLP, 2016)

A Theme-Rewriting Approach for Generating Algebra Word Problems. - Rik Koncel-Kedziorski; Ioannis Konstas; Luke Zettlemoyer; Hannaneh Hajishirzi (EMNLP, 2016)

Global Neural CCG Parsing with Optimality Guarantees. - Kenton Lee; Mike Lewis; Luke Zettlemoyer (EMNLP, 2016)

LSTM CCG Parsing. - Mike Lewis; Kenton Lee; Luke Zettlemoyer (HLT-NAACL, 2016)

Deep Semantic Role Labeling: What Works and What's Next. - Luheng He; Kenton Lee; Mike Lewis; Luke Zettlemoyer (ACL (1), 2017)

Learning a Neural Semantic Parser from User Feedback. - Srinivasan Iyer 001; Ioannis Konstas; Alvin Cheung; Jayant Krishnamurthy; Luke Zettlemoyer (ACL (1), 2017)

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension. - Mandar Joshi; Eunsol Choi; Daniel S. Weld; Luke Zettlemoyer (ACL (1), 2017)

Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. - Ioannis Konstas; Srinivasan Iyer 001; Mark Yatskar; Yejin Choi 001; Luke Zettlemoyer (ACL (1), 2017)

Zero-Shot Relation Extraction via Reading Comprehension. - Omer Levy; Minjoon Seo; Eunsol Choi; Luke Zettlemoyer (CoNLL, 2017)

Commonly Uncommon: Semantic Sparsity in Situation Recognition. - Mark Yatskar; Vicente Ordonez; Luke Zettlemoyer; Ali Farhadi (CVPR, 2017)

End-to-end Neural Coreference Resolution. - Kenton Lee; Luheng He; Mike Lewis; Luke Zettlemoyer (EMNLP, 2017)

Recurrent Additive Networks. - Kenton Lee; Omer Levy; Luke Zettlemoyer (CoRR, 2017)

Deep RNNs Encode Soft Hierarchical Syntax. - Terra Blevins; Omer Levy; Luke Zettlemoyer (ACL (2), 2018)

Neural Semantic Parsing. - Matt Gardner 001; Pradeep Dasigi; Srinivasan Iyer 001; Alane Suhr; Luke Zettlemoyer (ACL (5), 2018)

Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling. - Luheng He; Kenton Lee; Omer Levy; Luke Zettlemoyer (ACL (2), 2018)

Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum. - Omer Levy; Kenton Lee; Nicholas FitzGerald; Luke Zettlemoyer (ACL (2), 2018)

Ultra-Fine Entity Typing. - Eunsol Choi; Omer Levy; Yejin Choi 001; Luke Zettlemoyer (ACL (1), 2018)

Large-Scale QA-SRL Parsing. - Nicholas FitzGerald; Julian Michael; Luheng He; Luke Zettlemoyer (ACL (1), 2018)

QuAC: Question Answering in Context. - Eunsol Choi; He He 001; Mohit Iyyer; Mark Yatskar; Wen-tau Yih; Yejin Choi 001; Percy Liang; Luke Zettlemoyer (EMNLP, 2018)

Neural Metaphor Detection in Context. - Ge Gao; Eunsol Choi; Yejin Choi 001; Luke Zettlemoyer (EMNLP, 2018)

Mapping Language to Code in Programmatic Context. - Srinivasan Iyer 001; Ioannis Konstas; Alvin Cheung; Luke Zettlemoyer (EMNLP, 2018)

Dissecting Contextual Word Embeddings: Architecture and Representation. - Matthew E. Peters; Mark Neumann; Luke Zettlemoyer; Wen-tau Yih (EMNLP, 2018)

SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach. - Michael Petrochuk; Luke Zettlemoyer (EMNLP, 2018)

Syntactic Scaffolds for Semantic Structures. - Swabha Swayamdipta; Sam Thomson; Kenton Lee; Luke Zettlemoyer; Chris Dyer; Noah A. Smith (EMNLP, 2018)

NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System. - Xi Victoria Lin; Chenglong Wang; Luke Zettlemoyer; Michael D. Ernst (LREC, 2018)

Adversarial Example Generation with Syntactically Controlled Paraphrase Networks. - Mohit Iyyer; John Wieting; Kevin Gimpel; Luke Zettlemoyer (NAACL-HLT, 2018)

Higher-Order Coreference Resolution with Coarse-to-Fine Inference. - Kenton Lee; Luheng He; Luke Zettlemoyer (NAACL-HLT (2), 2018)

Crowdsourcing Question-Answer Meaning Representations. - Julian Michael; Gabriel Stanovsky; Luheng He; Ido Dagan; Luke Zettlemoyer (NAACL-HLT (2), 2018)

Deep Contextualized Word Representations. - Matthew E. Peters; Mark Neumann; Mohit Iyyer; Matt Gardner 001; Christopher Clark; Kenton Lee; Luke Zettlemoyer (NAACL-HLT, 2018)

Supervised Open Information Extraction. - Gabriel Stanovsky; Julian Michael; Luke Zettlemoyer; Ido Dagan (NAACL-HLT, 2018)

AllenNLP: A Deep Semantic Natural Language Processing Platform. - Matt Gardner 001; Joel Grus; Mark Neumann; Oyvind Tafjord; Pradeep Dasigi; Nelson F. Liu; Matthew E. Peters; Michael Schmitz 002; Luke Zettlemoyer (CoRR, 2018)

Recognizing and Imitating Programmer Style: Adversaries in Program Authorship Attribution. - Lucy Simko; Luke Zettlemoyer; Tadayoshi Kohno (Proc. Priv. Enhancing Technol., 2018)

Better Character Language Modeling through Morphology. - Terra Blevins; Luke Zettlemoyer (ACL (1), 2019)

The Referential Reader: A Recurrent Entity Network for Anaphora Resolution. - Fei Liu 023; Luke Zettlemoyer; Jacob Eisenstein (ACL (1), 2019)

Compositional Questions Do Not Necessitate Multi-hop Reasoning. - Sewon Min; Eric Wallace; Sameer Singh 001; Matt Gardner 001; Hannaneh Hajishirzi; Luke Zettlemoyer (ACL (1), 2019)

Multi-hop Reading Comprehension through Question Decomposition and Rescoring. - Sewon Min; Victor Zhong; Luke Zettlemoyer; Hannaneh Hajishirzi (ACL (1), 2019)

Evaluating Gender Bias in Machine Translation. - Gabriel Stanovsky; Noah A. Smith; Luke Zettlemoyer (ACL (1), 2019)

E3: Entailment-driven Extracting and Editing for Conversational Machine Reading. - Victor Zhong; Luke Zettlemoyer (ACL (1), 2019)

Vision-and-Dialog Navigation. - Jesse Thomason; Michael Murray; Maya Cakmak; Luke Zettlemoyer (CoRL, 2019)

JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation. - Rajas Agashe; Srinivasan Iyer 001; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

Cloze-driven Pretraining of Self-attention Networks. - Alexei Baevski; Sergey Edunov; Yinhan Liu; Luke Zettlemoyer; Michael Auli (EMNLP/IJCNLP (1), 2019)

Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases. - Christopher Clark; Mark Yatskar; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

Mask-Predict: Parallel Decoding of Conditional Masked Language Models. - Marjan Ghazvininejad; Omer Levy; Yinhan Liu; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

Learning Programmatic Idioms for Scalable Semantic Parsing. - Srinivasan Iyer 001; Alvin Cheung; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

BERT for Coreference Resolution: Baselines and Analysis. - Mandar Joshi; Omer Levy; Luke Zettlemoyer; Daniel S. Weld (EMNLP/IJCNLP (1), 2019)

A Discrete Hard EM Approach for Weakly Supervised Question Answering. - Sewon Min; Danqi Chen 001; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog. - Panupong Pasupat; Sonal Gupta; Karishma Mandyam; Rushin Shah; Mike Lewis; Luke Zettlemoyer (EMNLP/IJCNLP (1), 2019)

Iterative Search for Weakly Supervised Semantic Parsing. - Pradeep Dasigi; Matt Gardner 001; Shikhar Murty; Luke Zettlemoyer; Eduard H. Hovy (NAACL-HLT (1), 2019)

pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference. - Mandar Joshi; Eunsol Choi; Omer Levy; Daniel S. Weld; Luke Zettlemoyer (NAACL-HLT (1), 2019)

Improving Semantic Parsing for Task Oriented Dialog. - Arash Einolghozati; Panupong Pasupat; Sonal Gupta; Rushin Shah; Mrinal Mohit; Mike Lewis; Luke Zettlemoyer (CoRR, 2019)

Constant-Time Machine Translation with Conditional Masked Language Models. - Marjan Ghazvininejad; Omer Levy; Yinhan Liu; Luke Zettlemoyer (CoRR, 2019)

Transformers with convolutional context for ASR. - Abdelrahman Mohamed; Dmytro Okhonko; Luke Zettlemoyer (CoRR, 2019)

Sparse Networks from Scratch: Faster Training without Losing Performance. - Tim Dettmers; Luke Zettlemoyer (CoRR, 2019)

RoBERTa: A Robustly Optimized BERT Pretraining Approach. - Yinhan Liu; Myle Ott; Naman Goyal 001; Jingfei Du; Mandar Joshi; Danqi Chen 001; Omer Levy; Mike Lewis; Luke Zettlemoyer; Veselin Stoyanov (CoRR, 2019)

Crowdsourcing a High-Quality Gold Standard for QA-SRL. - Paul Roit; Ayal Klein; Daniela Stepanov; Jonathan Mamou; Julian Michael; Gabriel Stanovsky; Luke Zettlemoyer; Ido Dagan (CoRR, 2019)

Enforcing Encoder-Decoder Modularity in Sequence-to-Sequence Models. - Siddharth Dalmia; Abdelrahman Mohamed; Mike Lewis; Florian Metze; Luke Zettlemoyer (CoRR, 2019)

Zero-shot Entity Linking with Dense Entity Retrieval. - Ledell Wu; Fabio Petroni; Martin Josifoski; Sebastian Riedel 001; Luke Zettlemoyer (CoRR, 2019)

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering. - Sewon Min; Danqi Chen 001; Luke Zettlemoyer; Hannaneh Hajishirzi (CoRR, 2019)

Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders. - Terra Blevins; Luke Zettlemoyer (ACL, 2020)

Unsupervised Cross-lingual Representation Learning at Scale. - Alexis Conneau; Kartikay Khandelwal; Naman Goyal 001; Vishrav Chaudhary; Guillaume Wenzek; Francisco Guzmán; Edouard Grave; Myle Ott; Luke Zettlemoyer; Veselin Stoyanov (ACL, 2020)

Emerging Cross-lingual Structure in Pretrained Language Models. - Alexis Conneau; Shijie Wu; Haoran Li 007; Luke Zettlemoyer; Veselin Stoyanov (ACL, 2020)

Simple and Effective Retrieve-Edit-Rerank Text Generation. - Nabil Hossain; Marjan Ghazvininejad; Luke Zettlemoyer (ACL, 2020)

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. - Mike Lewis; Yinhan Liu; Naman Goyal 001; Marjan Ghazvininejad; Abdelrahman Mohamed; Omer Levy; Veselin Stoyanov; Luke Zettlemoyer (ACL, 2020)

Active Learning for Coreference Resolution using Discrete Annotation. - Belinda Z. Li; Gabriel Stanovsky; Luke Zettlemoyer (ACL, 2020)

Controlled Crowdsourcing for High-Quality QA-SRL Annotation. - Paul Roit; Ayal Klein; Daniela Stepanov; Jonathan Mamou; Julian Michael; Gabriel Stanovsky; Luke Zettlemoyer; Ido Dagan (ACL, 2020)

QANom: Question-Answer driven SRL for Nominalizations. - Ayal Klein; Jonathan Mamou; Valentina Pyatkin; Daniela Stepanov; Hangfeng He 001; Dan Roth 001; Luke Zettlemoyer; Ido Dagan (COLING, 2020)

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks. - Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer; Dieter Fox (CVPR, 2020)

Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing. - Xilun Chen 002; Asish Ghoshal; Yashar Mehdad; Luke Zettlemoyer; Sonal Gupta (EMNLP (1), 2020)

Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles. - Christopher Clark; Mark Yatskar; Luke Zettlemoyer (EMNLP (Findings), 2020)

AmbigQA: Answering Ambiguous Open-domain Questions. - Sewon Min; Julian Michael; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP (1), 2020)

An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction. - Bhargavi Paranjape; Mandar Joshi; John Thickstun; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP (1), 2020)

Scalable Zero-shot Entity Linking with Dense Entity Retrieval. - Ledell Wu; Fabio Petroni; Martin Josifoski; Sebastian Riedel 001; Luke Zettlemoyer (EMNLP (1), 2020)

Grounded Adaptation for Zero-shot Executable Semantic Parsing. - Victor Zhong; Mike Lewis; Sida I. Wang; Luke Zettlemoyer (EMNLP (1), 2020)

Generalization through Memorization: Nearest Neighbor Language Models. - Urvashi Khandelwal; Omer Levy; Dan Jurafsky; Luke Zettlemoyer; Mike Lewis (ICLR, 2020)

Aligned Cross Entropy for Non-Autoregressive Machine Translation. - Marjan Ghazvininejad; Vladimir Karpukhin; Luke Zettlemoyer; Omer Levy (ICML, 2020)

Pre-training via Paraphrasing. - Mike Lewis; Marjan Ghazvininejad; Gargi Ghosh; Armen Aghajanyan; Sida Wang 001; Luke Zettlemoyer (NeurIPS, 2020)

Semi-Autoregressive Training Improves Mask-Predict Decoding. - Marjan Ghazvininejad; Omer Levy; Luke Zettlemoyer (CoRR, 2020)

Moving Down the Long Tail of Word Sense Disambiguation with Gloss-Informed Biencoders. - Terra Blevins; Luke Zettlemoyer (CoRR, 2020)

DeLighT: Very Deep and Light-weight Transformer. - Sachin Mehta; Marjan Ghazvininejad; Srinivasan Iyer 001; Luke Zettlemoyer; Hannaneh Hajishirzi (CoRR, 2020)

Detecting Hallucinated Content in Conditional Neural Sequence Generation. - Chunting Zhou; Graham Neubig; Jiatao Gu; Mona T. Diab; Paco Guzman; Luke Zettlemoyer; Marjan Ghazvininejad (CoRR, 2020)

SpanBERT: Improving Pre-training by Representing and Predicting Spans. - Mandar Joshi; Danqi Chen 001; Yinhan Liu; Daniel S. Weld; Luke Zettlemoyer; Omer Levy (Trans. Assoc. Comput. Linguistics, 2020)

Multilingual Denoising Pre-training for Neural Machine Translation. - Yinhan Liu; Jiatao Gu; Naman Goyal 001; Xian Li 003; Sergey Edunov; Marjan Ghazvininejad; Mike Lewis; Luke Zettlemoyer (Trans. Assoc. Comput. Linguistics, 2020)

Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning. - Armen Aghajanyan; Sonal Gupta; Luke Zettlemoyer (ACL/IJCNLP (1), 2021)

Inducing Semantic Roles Without Syntax. - Julian Michael; Luke Zettlemoyer (ACL/IJCNLP (Findings), 2021)

Prompting Contrastive Explanations for Commonsense Reasoning Tasks. - Bhargavi Paranjape; Julian Michael; Marjan Ghazvininejad; Hannaneh Hajishirzi; Luke Zettlemoyer (ACL/IJCNLP (Findings), 2021)

DESCGEN: A Distantly Supervised Datasetfor Generating Entity Descriptions. - Weijia Shi; Mandar Joshi; Luke Zettlemoyer (ACL/IJCNLP (1), 2021)

Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment. - Haoyue Shi 001; Luke Zettlemoyer; Sida I. Wang (ACL/IJCNLP (1), 2021)

VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding. - Hu Xu 001; Gargi Ghosh; Po-Yao Huang 001; Prahal Arora; Masoumeh Aminzadeh; Christoph Feichtenhofer; Florian Metze; Luke Zettlemoyer (ACL/IJCNLP (Findings), 2021)

Detecting Hallucinated Content in Conditional Neural Sequence Generation. - Chunting Zhou; Graham Neubig; Jiatao Gu; Mona T. Diab; Francisco Guzmán; Luke Zettlemoyer; Marjan Ghazvininejad (ACL/IJCNLP (Findings), 2021)

Language Grounding with 3D Objects. - Jesse Thomason; Mohit Shridhar; Yonatan Bisk; Chris Paxton 001; Luke Zettlemoyer (CoRL, 2021)

FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary. - Terra Blevins; Mandar Joshi; Luke Zettlemoyer (EACL, 2021)

Muppet: Massive Multi-task Representations with Pre-Finetuning. - Armen Aghajanyan; Anchit Gupta; Akshat Shrivastava; Xilun Chen 002; Luke Zettlemoyer; Sonal Gupta (EMNLP (1), 2021)

Surface Form Competition: Why the Highest Probability Answer Isn't Always Right. - Ari Holtzman; Peter West; Vered Shwartz; Yejin Choi 001; Luke Zettlemoyer (EMNLP (1), 2021)

VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding. - Hu Xu 001; Gargi Ghosh; Po-Yao Huang 001; Dmytro Okhonko; Armen Aghajanyan; Florian Metze; Luke Zettlemoyer; Christoph Feichtenhofer (EMNLP (1), 2021)

Better Fine-Tuning by Reducing Representational Collapse. - Armen Aghajanyan; Akshat Shrivastava; Anchit Gupta; Naman Goyal 001; Luke Zettlemoyer; Sonal Gupta (ICLR, 2021)

Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing. - Asish Ghoshal; Xilun Chen 002; Sonal Gupta; Luke Zettlemoyer; Yashar Mehdad (ICLR, 2021)

Nearest Neighbor Machine Translation. - Urvashi Khandelwal; Angela Fan; Dan Jurafsky; Luke Zettlemoyer; Mike Lewis (ICLR, 2021)

DeLighT: Deep and Light-weight Transformer. - Sachin Mehta; Marjan Ghazvininejad; Srinivasan Iyer 001; Luke Zettlemoyer; Hannaneh Hajishirzi (ICLR, 2021)

BASE Layers: Simplifying Training of Large, Sparse Models. - Mike Lewis; Shruti Bhosale; Tim Dettmers; Naman Goyal 001; Luke Zettlemoyer (ICML, 2021)

Luna: Linear Unified Nested Attention. - Xuezhe Ma; Xiang Kong; Sinong Wang; Chunting Zhou; Jonathan May; Hao Ma 001; Luke Zettlemoyer (NeurIPS, 2021)

SILG: The Multi-domain Symbolic Interactive Language Grounding Benchmark. - Victor Zhong; Austin W. Hanjie; Sida I. Wang; Karthik Narasimhan; Luke Zettlemoyer (NeurIPS, 2021)

DESCGEN: A Distantly Supervised Dataset for Generating Abstractive Entity Descriptions. - Weijia Shi; Mandar Joshi; Luke Zettlemoyer (CoRR, 2021)

SILG: The Multi-environment Symbolic Interactive Language Grounding Benchmark. - Victor Zhong; Austin W. Hanjie; Sida I. Wang; Karthik Narasimhan; Luke Zettlemoyer (CoRR, 2021)

Reducing Target Group Bias in Hate Speech Detectors. - Darsh J. Shah; Sinong Wang; Han Fang; Hao Ma 001; Luke Zettlemoyer (CoRR, 2021)

Few-shot Learning with Multilingual Language Models. - Xi Victoria Lin; Todor Mihaylov; Mikel Artetxe; Tianlu Wang; Shuohui Chen; Daniel Simig; Myle Ott; Naman Goyal 001; Shruti Bhosale; Jingfei Du; Ramakanth Pasunuru; Sam Shleifer; et al. (CoRR, 2021)

Efficient Large Scale Language Modeling with Mixtures of Experts. - Mikel Artetxe; Shruti Bhosale; Naman Goyal 001; Todor Mihaylov; Myle Ott; Sam Shleifer; Xi Victoria Lin; Jingfei Du; Srinivasan Iyer 001; Ramakanth Pasunuru; Giri Anantharaman; Xian Li 003; et al. (CoRR, 2021)

Question Answering Infused Pre-training of General-Purpose Contextualized Representations. - Robin Jia; Mike Lewis; Luke Zettlemoyer (ACL (Findings), 2022)

Prompt-free and Efficient Few-shot Learning with Language Models. - Rabeeh Karimi Mahabadi; Luke Zettlemoyer; James Henderson 001; Lambert Mathias; Marzieh Saeidi; Veselin Stoyanov; Majid Yazdani (ACL (1), 2022)

Noisy Channel Language Model Prompting for Few-Shot Text Classification. - Sewon Min; Mike Lewis; Hannaneh Hajishirzi; Luke Zettlemoyer (ACL (1), 2022)

FaVIQ: FAct Verification from Information-seeking Questions. - Jungsoo Park; Sewon Min; Jaewoo Kang; Luke Zettlemoyer; Hannaneh Hajishirzi (ACL (1), 2022)

Efficient Large Scale Language Modeling with Mixtures of Experts. - Mikel Artetxe; Shruti Bhosale; Naman Goyal 001; Todor Mihaylov; Myle Ott; Sam Shleifer; Xi Victoria Lin; Jingfei Du; Srinivasan Iyer 001; Ramakanth Pasunuru; Giridharan Anantharaman; Xian Li 003; et al. (EMNLP, 2022)

On the Role of Bidirectionality in Language Model Pre-Training. - Mikel Artetxe; Jingfei Du; Naman Goyal 001; Luke Zettlemoyer; Veselin Stoyanov (EMNLP (Findings), 2022)

Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models. - Terra Blevins; Hila Gonen; Luke Zettlemoyer (EMNLP, 2022)

Language Contamination Helps Explains the Cross-lingual Capabilities of English Pretrained Models. - Terra Blevins; Luke Zettlemoyer (EMNLP, 2022)

CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation. - Tanay Dixit; Bhargavi Paranjape; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP (Findings), 2022)

Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection. - Suchin Gururangan; Dallas Card; Sarah K. Dreier; Emily K. Gade; Leroy Z. Wang; Zeyu Wang; Luke Zettlemoyer; Noah A. Smith (EMNLP, 2022)

Few-shot Learning with Multilingual Generative Language Models. - Xi Victoria Lin; Todor Mihaylov; Mikel Artetxe; Tianlu Wang; Shuohui Chen; Daniel Simig; Myle Ott; Naman Goyal 001; Shruti Bhosale; Jingfei Du; Ramakanth Pasunuru; Sam Shleifer; et al. (EMNLP, 2022)

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? - Sewon Min; Xinxi Lyu; Ari Holtzman; Mikel Artetxe; Mike Lewis; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP, 2022)

M2D2: A Massively Multi-Domain Language Modeling Dataset. - Machel Reid; Victor Zhong; Suchin Gururangan; Luke Zettlemoyer (EMNLP, 2022)

Improving Passage Retrieval with Zero-Shot Question Generation. - Devendra Singh Sachan; Mike Lewis; Mandar Joshi; Armen Aghajanyan; Wen-tau Yih; Joelle Pineau; Luke Zettlemoyer (EMNLP, 2022)

Natural Language to Code Translation with Execution. - Freda Shi; Daniel Fried; Marjan Ghazvininejad; Luke Zettlemoyer; Sida I. Wang (EMNLP, 2022)

Nearest Neighbor Zero-Shot Inference. - Weijia Shi; Julian Michael; Suchin Gururangan; Luke Zettlemoyer (EMNLP, 2022)

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. - Tianbao Xie; Chen Henry Wu; Peng Shi 010; Ruiqi Zhong; Torsten Scholak; Michihiro Yasunaga; Chien-Sheng Wu; Ming Zhong 005; Pengcheng Yin; Sida I. Wang; Victor Zhong; Bailin Wang; et al. (EMNLP, 2022)

HTLM: Hyper-Text Pre-Training and Prompting of Language Models. - Armen Aghajanyan; Dmytro Okhonko; Mike Lewis; Mandar Joshi; Hu Xu 001; Gargi Ghosh; Luke Zettlemoyer (ICLR, 2022)

8-bit Optimizers via Block-wise Quantization. - Tim Dettmers; Mike Lewis; Sam Shleifer; Luke Zettlemoyer (ICLR, 2022)

BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation. - Eleftheria Briakou; Sida I. Wang; Luke Zettlemoyer; Marjan Ghazvininejad (NAACL-HLT (Findings), 2022)

DEMix Layers: Disentangling Domains for Modular Language Modeling. - Suchin Gururangan; Mike Lewis; Ari Holtzman; Noah A. Smith; Luke Zettlemoyer (NAACL-HLT, 2022)

Quantifying Adaptability in Pre-trained Language Models with 500 Tasks. - Belinda Z. Li; Jane A. Yu; Madian Khabsa; Luke Zettlemoyer; Alon Y. Halevy; Jacob Andreas (NAACL-HLT, 2022)

MetaICL: Learning to Learn In Context. - Sewon Min; Mike Lewis; Luke Zettlemoyer; Hannaneh Hajishirzi (NAACL-HLT, 2022)

GPT3.int8(): 8-bit Matrix Multiplication for Transformers at Scale. - Tim Dettmers; Mike Lewis; Younes Belkada; Luke Zettlemoyer (NeurIPS, 2022)

Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. - Kushal Tirumala; Aram H. Markosyan; Luke Zettlemoyer; Armen Aghajanyan (NeurIPS, 2022)

Improving Policy Learning via Language Dynamics Distillation. - Victor Zhong; Jesse Mu; Luke Zettlemoyer; Edward Grefenstette; Tim Rocktäschel (NeurIPS, 2022)

Stop: A Dataset for Spoken Task Oriented Semantic Parsing. - Paden Tomasello; Akshat Shrivastava; Daniel Lazar; Po-Chun Hsu; Duc Le; Adithya Sagar; Ali Elkahky; Jade Copet; Wei-Ning Hsu; Yossi Adi; Robin Algayres; Tu Anh Nguyen; et al. (SLT, 2022)

CM3: A Causal Masked Multimodal Model of the Internet. - Armen Aghajanyan; Bernie Huang; Candace Ross; Vladimir Karpukhin; Hu Xu 001; Naman Goyal 001; Dmytro Okhonko; Mandar Joshi; Gargi Ghosh; Mike Lewis; Luke Zettlemoyer (CoRR, 2022)

PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models. - Rabeeh Karimi Mahabadi; Luke Zettlemoyer; James Henderson 001; Marzieh Saeidi; Lambert Mathias; Veselin Stoyanov; Majid Yazdani (CoRR, 2022)

Language Contamination Explains the Cross-lingual Capabilities of English Pretrained Models. - Terra Blevins; Luke Zettlemoyer (CoRR, 2022)

OPT: Open Pre-trained Transformer Language Models. - Susan Zhang; Stephen Roller; Naman Goyal 001; Mikel Artetxe; Moya Chen; Shuohui Chen; Christopher Dewan; Mona T. Diab; Xian Li 003; Xi Victoria Lin; Todor Mihaylov; Myle Ott; et al. (CoRR, 2022)

Few-shot Mining of Naturally Occurring Inputs and Outputs. - Mandar Joshi; Terra Blevins; Mike Lewis; Daniel S. Weld; Luke Zettlemoyer (CoRR, 2022)

STOP: A dataset for Spoken Task Oriented Semantic Parsing. - Paden Tomasello; Akshat Shrivastava; Daniel Lazar; Po-Chun Hsu; Duc Le; Adithya Sagar; Ali Elkahky; Jade Copet; Wei-Ning Hsu; Yossef Mordechay; Robin Algayres; Tu Anh Nguyen; et al. (CoRR, 2022)

Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models. - Margaret Li; Suchin Gururangan; Tim Dettmers; Mike Lewis; Tim Althoff; Noah A. Smith; Luke Zettlemoyer (CoRR, 2022)

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale. - Tim Dettmers; Mike Lewis; Younes Belkada; Luke Zettlemoyer (CoRR, 2022)

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization. - Srinivasan Iyer 001; Xi Victoria Lin; Ramakanth Pasunuru; Todor Mihaylov; Daniel Simig; Ping Yu; Kurt Shuster 001; Tianlu Wang; Qing Liu; Punit Singh Koura; Xian Li 003; Brian O'Horo; et al. (CoRR, 2022)

Multilingual Autoregressive Entity Linking. - Nicola De Cao; Ledell Wu; Kashyap Popat; Mikel Artetxe; Naman Goyal 001; Mikhail Plekhanov; Luke Zettlemoyer; Nicola Cancedda; Sebastian Riedel 001; Fabio Petroni (Trans. Assoc. Comput. Linguistics, 2022)

Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. - Suzanna Sia; Anton Belyy; Amjad Almahairi; Madian Khabsa; Luke Zettlemoyer; Lambert Mathias (AAAI, 2023)

CREPE: Open-Domain Question Answering with False Presuppositions. - Xinyan Yu 001; Sewon Min; Luke Zettlemoyer; Hannaneh Hajishirzi (ACL (1), 2023)

In-context Examples Selection for Machine Translation. - Sweta Agrawal; Chunting Zhou; Mike Lewis; Luke Zettlemoyer; Marjan Ghazvininejad (ACL (Findings), 2023)

Prompting Language Models for Linguistic Structure. - Terra Blevins; Hila Gonen; Luke Zettlemoyer (ACL (1), 2023)

Contrastive Decoding: Open-ended Text Generation as Optimization. - Xiang Lisa Li; Ari Holtzman; Daniel Fried; Percy Liang; Jason Eisner; Tatsunori Hashimoto; Luke Zettlemoyer; Mike Lewis (ACL (1), 2023)

Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations. - Xinxi Lyu; Sewon Min; Iz Beltagy; Luke Zettlemoyer; Hannaneh Hajishirzi (ACL (1), 2023)

Nonparametric Masked Language Modeling. - Sewon Min; Weijia Shi; Mike Lewis; Xilun Chen 002; Wen-tau Yih; Hannaneh Hajishirzi; Luke Zettlemoyer (ACL (Findings), 2023)

One Embedder, Any Task: Instruction-Finetuned Text Embeddings. - Hongjin Su; Weijia Shi; Jungo Kasai; Yizhong Wang; Yushi Hu; Mari Ostendorf; Wen-tau Yih; Noah A. Smith; Luke Zettlemoyer; Tao Yu 009 (ACL (Findings), 2023)

Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters. - Boshi Wang; Sewon Min; Xiang Deng 001; Jiaming Shen; You Wu 001; Luke Zettlemoyer; Huan Sun 001 (ACL (1), 2023)

Training Trajectories of Language Models Across Scales. - Mengzhou Xia; Mikel Artetxe; Chunting Zhou; Xi Victoria Lin; Ramakanth Pasunuru; Danqi Chen 001; Luke Zettlemoyer; Veselin Stoyanov (ACL (1), 2023)

Revisiting Machine Translation for Cross-lingual Classification. - Mikel Artetxe; Vedanuj Goswami; Shruti Bhosale; Angela Fan; Luke Zettlemoyer (EMNLP, 2023)

Demystifying Prompts in Language Models via Perplexity Estimation. - Hila Gonen; Srini Iyer 001; Terra Blevins; Noah A. Smith; Luke Zettlemoyer (EMNLP (Findings), 2023)

XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models. - Davis Liang; Hila Gonen; Yuning Mao; Rui Hou; Naman Goyal 001; Marjan Ghazvininejad; Luke Zettlemoyer; Madian Khabsa (EMNLP, 2023)

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. - Sewon Min; Kalpesh Krishna; Xinxi Lyu; Mike Lewis; Wen-tau Yih; Pang Wei Koh; Mohit Iyyer; Luke Zettlemoyer; Hannaneh Hajishirzi (EMNLP, 2023)

Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too? - Weijia Shi; Xiaochuang Han; Hila Gonen; Ari Holtzman; Yulia Tsvetkov; Luke Zettlemoyer (EMNLP (Findings), 2023)

Getting MoRE out of Mixture of Language Model Reasoning Experts. - Chenglei Si; Weijia Shi; Chen Zhao 009; Luke Zettlemoyer; Jordan L. Boyd-Graber (EMNLP (Findings), 2023)

RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering. - Victor Zhong; Weijia Shi; Wen-tau Yih; Luke Zettlemoyer (EMNLP (Findings), 2023)

CiT: Curation in Training for Effective Vision-Language Data. - Hu Xu 001; Saining Xie; Po-Yao Huang 001; Licheng Yu; Russell Howes; Gargi Ghosh; Luke Zettlemoyer; Christoph Feichtenhofer (ICCV, 2023)

Binding Language Models in Symbolic Languages. - Zhoujun Cheng; Tianbao Xie; Peng Shi 010; Chengzu Li; Rahul Nadkarni; Yushi Hu; Caiming Xiong; Dragomir Radev; Mari Ostendorf; Luke Zettlemoyer; Noah A. Smith; Tao Yu 009 (ICLR, 2023)

InCoder: A Generative Model for Code Infilling and Synthesis. - Daniel Fried; Armen Aghajanyan; Jessy Lin; Sida Wang 001; Eric Wallace; Freda Shi; Ruiqi Zhong; Scott Yih; Luke Zettlemoyer; Mike Lewis (ICLR, 2023)

ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning. - Olga Golovneva; Moya Chen; Spencer Poff; Martin Corredor; Luke Zettlemoyer; Maryam Fazel-Zarandi; Asli Celikyilmaz (ICLR, 2023)

Mega: Moving Average Equipped Gated Attention. - Xuezhe Ma; Chunting Zhou; Xiang Kong; Junxian He; Liangke Gui; Graham Neubig; Jonathan May; Luke Zettlemoyer (ICLR, 2023)

AGRO: Adversarial discovery of error-prone Groups for Robust Optimization. - Bhargavi Paranjape; Pradeep Dasigi; Vivek Srikumar; Luke Zettlemoyer; Hannaneh Hajishirzi (ICLR, 2023)

Selective Annotation Makes Language Models Better Few-Shot Learners. - Hongjin Su; Jungo Kasai; Chen Henry Wu; Weijia Shi; Tianlu Wang; Jiayi Xin; Rui Zhang 037; Mari Ostendorf; Luke Zettlemoyer; Noah A. Smith; Tao Yu 009 (ICLR, 2023)

Scaling Laws for Generative Mixed-Modal Language Models. - Armen Aghajanyan; Lili Yu; Alexis Conneau; Wei-Ning Hsu; Karen Hambardzumyan; Susan Zhang; Stephen Roller; Naman Goyal 001; Omer Levy; Luke Zettlemoyer (ICML, 2023)

The case for 4-bit precision: k-bit Inference Scaling Laws. - Tim Dettmers; Luke Zettlemoyer (ICML, 2023)

DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. - Yuhang Lai; Chengxi Li 011; Yiming Wang; Tianyi Zhang; Ruiqi Zhong; Luke Zettlemoyer; Wen-Tau Yih; Daniel Fried; Sida I. Wang; Tao Yu 009 (ICML, 2023)

Retrieval-Augmented Multimodal Language Modeling. - Michihiro Yasunaga; Armen Aghajanyan; Weijia Shi; Richard James 001; Jure Leskovec; Percy Liang; Mike Lewis; Luke Zettlemoyer; Wen-Tau Yih (ICML, 2023)

QLoRA: Efficient Finetuning of Quantized LLMs. - Tim Dettmers; Artidoro Pagnoni; Ari Holtzman; Luke Zettlemoyer (NeurIPS, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Eric Hambro; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (NeurIPS, 2023)

Stable and low-precision training for large-scale vision-language models. - Mitchell Wortsman; Tim Dettmers; Luke Zettlemoyer; Ari Morcos; Ali Farhadi; Ludwig Schmidt (NeurIPS, 2023)

MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. - Lili Yu; Daniel Simig; Colin Flaherty; Armen Aghajanyan; Luke Zettlemoyer; Mike Lewis (NeurIPS, 2023)

LIMA: Less Is More for Alignment. - Chunting Zhou; Pengfei Liu; Puxin Xu; Srinivasan Iyer 001; Jiao Sun; Yuning Mao; Xuezhe Ma; Avia Efrat; Ping Yu; Lili Yu; Susan Zhang; Gargi Ghosh; et al. (NeurIPS, 2023)

The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages. - Benjamin Muller; Belen Alastruey; Prangthip Hansanti; Elahe Kalbassi; Christophe Ropers; Eric Michael Smith; Adina Williams; Luke Zettlemoyer; Pierre Andrews; Marta R. Costa-jussà (WMT, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (CoRR, 2023)

Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation. - Marjan Ghazvininejad; Hila Gonen; Luke Zettlemoyer (CoRR, 2023)

ART: Automatic multi-step reasoning and tool-use for large language models. - Bhargavi Paranjape; Scott M. Lundberg; Sameer Singh 001; Hannaneh Hajishirzi; Luke Zettlemoyer; Marco Túlio Ribeiro (CoRR, 2023)

Scaling Expert Language Models with Unsupervised Domain Discovery. - Suchin Gururangan; Margaret Li; Mike Lewis; Weijia Shi; Tim Althoff; Noah A. Smith; Luke Zettlemoyer (CoRR, 2023)

Mixture of Prompt Experts for Generalizable and Interpretable Question Answering. - Chenglei Si; Weijia Shi; Chen Zhao 009; Luke Zettlemoyer; Jordan L. Boyd-Graber (CoRR, 2023)

Generative Models as a Complex Systems Science: How can we make sense of large language model behavior? - Ari Holtzman; Peter West; Luke Zettlemoyer (CoRR, 2023)

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. - Sewon Min; Suchin Gururangan; Eric Wallace; Hannaneh Hajishirzi; Noah A. Smith; Luke Zettlemoyer (CoRR, 2023)

Shepherd: A Critic for Language Model Generation. - Tianlu Wang; Ping Yu; Xiaoqing Ellen Tan; Sean O'Brien; Ramakanth Pasunuru; Jane Dwivedi-Yu; Olga Golovneva; Luke Zettlemoyer; Maryam Fazel-Zarandi; Asli Celikyilmaz (CoRR, 2023)

Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. - Lili Yu; Bowen Shi; Ramakanth Pasunuru; Benjamin Muller; Olga Golovneva; Tianlu Wang; Arun Babu; Binh Tang; Brian Karrer; Shelly Sheynin; Candace Ross; Adam Polyak; et al. (CoRR, 2023)

Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging. - Joel Jang; Seungone Kim; Bill Yuchen Lin; Yizhong Wang; Jack Hessel; Luke Zettlemoyer; Hannaneh Hajishirzi; Yejin Choi 001; Prithviraj Ammanabrolu (CoRR, 2023)

PathFinder: Guided Search over Multi-Step Reasoning Paths. - Olga Golovneva; Sean O'Brien; Ramakanth Pasunuru; Tianlu Wang; Luke Zettlemoyer; Maryam Fazel-Zarandi; Asli Celikyilmaz (CoRR, 2023)

Questions Are All You Need to Train a Dense Passage Retriever. - Devendra Singh Sachan; Mike Lewis; Dani Yogatama; Luke Zettlemoyer; Joelle Pineau; Manzil Zaheer (Trans. Assoc. Comput. Linguistics, 2023)

LegoNN: Building Modular Encoder-Decoder Models. - Siddharth Dalmia; Dmytro Okhonko; Mike Lewis; Sergey Edunov; Shinji Watanabe 001; Florian Metze; Luke Zettlemoyer; Abdelrahman Mohamed (IEEE ACM Trans. Audio Speech Lang. Process., 2023)

The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. - Lucas Bandarkar; Davis Liang; Benjamin Muller; Mikel Artetxe; Satya Narayan Shukla; Donald Husa; Naman Goyal 001; Abhinandan Krishnan; Luke Zettlemoyer; Madian Khabsa (ACL (1), 2024)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Evan Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (ACL (1), 2024)

MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling. - Tomasz Limisiewicz; Terra Blevins; Hila Gonen; Orevaoghene Ahia; Luke Zettlemoyer (ACL (1), 2024)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

MoDE: CLIP Data Experts via Clustering. - Jiawei Ma; Po-Yao Huang 001; Saining Xie; Shang-Wen Li 001; Luke Zettlemoyer; Shih-Fu Chang; Wen-Tau Yih; Hu Xu 001 (CVPR, 2024)

Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation with Pretrained Language Models. - Haoqiang Kang; Terra Blevins; Luke Zettlemoyer (EACL (1), 2024)

Altogether: Image Captioning via Re-aligning Alt-text. - Hu Xu 001; Po-Yao Huang 001; Xiaoqing Ellen Tan; Ching-Feng Yeh; Jacob Kahn; Christine Jou; Gargi Ghosh; Omer Levy; Luke Zettlemoyer; Wen-tau Yih; Shang-Wen Li 001; Saining Xie; et al. (EMNLP, 2024)

Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models. - Terra Blevins; Tomasz Limisiewicz; Suchin Gururangan; Margaret Li; Hila Gonen; Noah A. Smith; Luke Zettlemoyer (EMNLP, 2024)

CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation. - Tong Chen; Akari Asai; Niloofar Mireshghallah; Sewon Min; James Grimmelmann; Yejin Choi 001; Hannaneh Hajishirzi; Luke Zettlemoyer; Pang Wei Koh (EMNLP, 2024)

Better Alignment with Instruction Back-and-Forth Translation. - Thao Nguyen; Jeffrey Li; Sewoong Oh; Ludwig Schmidt; Jason Weston; Luke Zettlemoyer; Xian Li 003 (EMNLP (Findings), 2024)

Representation Deficiency in Masked Language Modeling. - Yu Meng 001; Jitin Krishnan; Sinong Wang; Qifan Wang 001; Yuning Mao; Han Fang; Marjan Ghazvininejad; Jiawei Han 001; Luke Zettlemoyer (ICLR, 2024)

Demystifying CLIP Data. - Hu Xu 001; Saining Xie; Xiaoqing Ellen Tan; Po-Yao Huang 001; Russell Howes; Vasu Sharma; Shang-Wen Li 001; Gargi Ghosh; Luke Zettlemoyer; Christoph Feichtenhofer (ICLR, 2024)

Self-Alignment with Instruction Backtranslation. - Xian Li 003; Ping Yu; Chunting Zhou; Timo Schick; Omer Levy; Luke Zettlemoyer; Jason Weston; Mike Lewis (ICLR, 2024)

RA-DIT: Retrieval-Augmented Dual Instruction Tuning. - Xi Victoria Lin; Xilun Chen 002; Mingda Chen; Weijia Shi; Maria Lomeli; Richard James 001; Pedro Rodriguez 001; Jacob Kahn; Gergely Szilvasy; Mike Lewis; Luke Zettlemoyer; Wen-tau Yih (ICLR, 2024)

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. - Sewon Min; Suchin Gururangan; Eric Wallace; Weijia Shi; Hannaneh Hajishirzi; Noah A. Smith; Luke Zettlemoyer (ICLR, 2024)

Detecting Pretraining Data from Large Language Models. - Weijia Shi; Anirudh Ajith; Mengzhou Xia; Yangsibo Huang; Daogao Liu; Terra Blevins; Danqi Chen 001; Luke Zettlemoyer (ICLR, 2024)

In-Context Pretraining: Language Modeling Beyond Document Boundaries. - Weijia Shi; Sewon Min; Maria Lomeli; Chunting Zhou; Margaret Li; Xi Victoria Lin; Noah A. Smith; Luke Zettlemoyer; Wen-tau Yih; Mike Lewis (ICLR, 2024)

Trusting Your Evidence: Hallucinate Less with Context-aware Decoding. - Weijia Shi; Xiaochuang Han; Mike Lewis; Yulia Tsvetkov; Luke Zettlemoyer; Wen-tau Yih (NAACL (Short Papers), 2024)

REPLUG: Retrieval-Augmented Black-Box Language Models. - Weijia Shi; Sewon Min; Michihiro Yasunaga; Minjoon Seo; Richard James 001; Mike Lewis; Luke Zettlemoyer; Wen-tau Yih (NAACL-HLT, 2024)

Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models. - Yushi Hu; Weijia Shi; Xingyu Fu; Dan Roth 001; Mari Ostendorf; Luke Zettlemoyer; Noah A. Smith; Ranjay Krishna (NeurIPS, 2024)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. - Xuezhe Ma; Xiaomeng Yang; Wenhan Xiong; Beidi Chen; Lili Yu; Hao Zhang 025; Jonathan May; Luke Zettlemoyer; Omer Levy; Chunting Zhou (NeurIPS, 2024)

Scaling Retrieval-Based Language Models with a Trillion-Token Datastore. - Rulin Shao; Jacqueline He; Akari Asai; Weijia Shi; Tim Dettmers; Sewon Min; Luke Zettlemoyer; Pang Wei Koh (NeurIPS, 2024)

Evaluating Copyright Takedown Methods for Language Models. - Boyi Wei; Weijia Shi; Yangsibo Huang; Noah A. Smith; Chiyuan Zhang; Luke Zettlemoyer; Kai Li 001; Peter Henderson 002 (NeurIPS, 2024)

Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens. - Jiacheng Liu 010; Sewon Min; Luke Zettlemoyer; Yejin Choi 001; Hannaneh Hajishirzi (CoRR, 2024)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (CoRR, 2024)

Do Membership Inference Attacks Work on Large Language Models? - Michael Duan; Anshuman Suri; Niloofar Mireshghallah; Sewon Min; Weijia Shi; Luke Zettlemoyer; Yulia Tsvetkov; Yejin Choi 001; David Evans 001; Hannaneh Hajishirzi (CoRR, 2024)

Comparing Hallucination Detection Metrics for Multilingual Generation. - Haoqiang Kang; Terra Blevins; Luke Zettlemoyer (CoRR, 2024)

Reliable, Adaptable, and Attributable Language Models with Retrieval. - Akari Asai; Zexuan Zhong; Danqi Chen 001; Pang Wei Koh; Luke Zettlemoyer; Hannaneh Hajishirzi; Wen-tau Yih (CoRR, 2024)

Text Quality-Based Pruning for Efficient Training of Language Models. - Vasu Sharma; Karthik Padthe; Newsha Ardalani; Kushal Tirumala; Russell Howes; Hu Xu 001; Po-Yao Huang 001; Shang-Wen Li 001; Armen Aghajanyan; Gargi Ghosh; Luke Zettlemoyer (CoRR, 2024)

Computational Tradeoffs in Image Synthesis: Diffusion, Masked-Token, and Next-Token Prediction. - Maciej Kilian; Varun Jampani; Luke Zettlemoyer (CoRR, 2024)

MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts. - Xi Victoria Lin; Akshat Shrivastava; Liang Luo; Srinivasan Iyer 001; Mike Lewis; Gargi Ghosh; Luke Zettlemoyer; Armen Aghajanyan (CoRR, 2024)

The Root Shapes the Fruit: On the Persistence of Gender-Exclusive Harms in Aligned Language Models. - Anaelia Ovalle; Krunoslav Lehman Pavasovic; Louis Martin; Luke Zettlemoyer; Eric Michael Smith; Adina Williams; Levent Sagun (CoRR, 2024)

OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs. - Akari Asai; Jacqueline He; Rulin Shao; Weijia Shi; Amanpreet Singh; Joseph Chee Chang; Kyle Lo; Luca Soldaini; Sergey Feldman; Mike D'Arcy; David Wadden; Matt Latzke; et al. (CoRR, 2024)

Negative Token Merging: Image-based Adversarial Feature Guidance. - Jaskirat Singh; Lindsey Li; Weijia Shi; Ranjay Krishna; Yejin Choi 001; Pang Wei Koh; Michael F. Cohen; Stephen Gould; Liang Zheng 001; Luke Zettlemoyer (CoRR, 2024)

ALMA: Alignment with Minimal Annotation. - Michihiro Yasunaga; Leonid Shamis; Chunting Zhou; Andrew Cohen; Jason Weston; Luke Zettlemoyer; Marjan Ghazvininejad (CoRR, 2024)

Memory Layers at Scale. - Vincent-Pierre Berges; Barlas Oguz; Daniel Haziza; Wen-tau Yih; Luke Zettlemoyer; Gargi Ghosh (CoRR, 2024)

LMFusion: Adapting Pretrained Language Models for Multimodal Generation. - Weijia Shi; Xiaochuang Han; Chunting Zhou; Weixin Liang; Xi Victoria Lin; Luke Zettlemoyer; Lili Yu (CoRR, 2024)

When Worse is Better: Navigating the compression-generation tradeoff in visual tokenization. - Vivek Ramanujan; Kushal Tirumala; Armen Aghajanyan; Luke Zettlemoyer; Ali Farhadi (CoRR, 2024)

Improving Factuality with Explicit Working Memory. - Mingda Chen; Yang Li; Karthik Padthe; Rulin Shao; Alicia Sun; Luke Zettlemoyer; Gargi Gosh; Wen-tau Yih (CoRR, 2024)

Improving Factuality with Explicit Working Memory. - Mingda Chen; Yang Li; Karthik Padthe; Rulin Shao; Alicia Yi Sun; Luke Zettlemoyer; Gargi Ghosh; Wen-tau Yih (ACL (1), 2025)

Byte Latent Transformer: Patches Scale Better Than Tokens. - Artidoro Pagnoni; Ramakanth Pasunuru; Pedro Rodríguez 001; John Nguyen; Benjamin Muller; Margaret Li; Chunting Zhou; Lili Yu; Jason E. Weston; Luke Zettlemoyer; Gargi Ghosh; Mike Lewis; et al. (ACL (1), 2025)

The Root Shapes the Fruit: On the Persistence of Gender-Exclusive Harms in Aligned Language Models. - Anaelia Ovalle; Krunoslav Lehman Pavasovic; Louis Martin; Luke Zettlemoyer; Eric Michael Smith; Kai-Wei Chang; Adina Williams; Levent Sagun (FAccT, 2025)

Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass. - Tong Chen; Hao Fang 002; Patrick Xia 002; Xiaodong Liu 003; Benjamin Van Durme; Luke Zettlemoyer; Jianfeng Gao 001; Hao Cheng 002 (ICLR, 2025)

Fantastic Copyrighted Beasts and How (Not) to Generate Them. - Luxi He; Yangsibo Huang; Weijia Shi; Tinghao Xie; Haotian Liu; Yue Wang; Luke Zettlemoyer; Chiyuan Zhang; Danqi Chen 001; Peter Henderson 002 (ICLR, 2025)

(Mis)Fitting Scaling Laws: A Survey of Scaling Law Fitting Techniques in Deep Learning. - Margaret Li; Sneha Kudugunta; Luke Zettlemoyer (ICLR, 2025)

MUSE: Machine Unlearning Six-Way Evaluation for Language Models. - Weijia Shi; Jaechan Lee; Yangsibo Huang; Sadhika Malladi; Jieyu Zhao 001; Ari Holtzman; Daogao Liu; Luke Zettlemoyer; Noah A. Smith; Chiyuan Zhang (ICLR, 2025)

Latent Action Pretraining from Videos. - Seonghyeon Ye; Joel Jang; Byeongguk Jeon; Se June Joo; Jianwei Yang; Baolin Peng; Ajay Mandlekar; Reuben Tan; Yu-Wei Chao; Bill Yuchen Lin; Lars Liden; Kimin Lee; et al. (ICLR, 2025)

Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. - Chunting Zhou; Lili Yu; Arun Babu; Kushal Tirumala; Michihiro Yasunaga; Leonid Shamis; Jacob Kahn; Xuezhe Ma; Luke Zettlemoyer; Omer Levy (ICLR, 2025)

Does Liking Yellow Imply Driving a School Bus? Semantic Leakage in Language Models. - Hila Gonen; Terra Blevins; Alisa Liu; Luke Zettlemoyer; Noah A. Smith (NAACL (Long Papers), 2025)

Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models. - Weixin Liang; Lili Yu; Liang Luo; Srini Iyer 001; Ning Dong; Chunting Zhou; Gargi Ghosh; Mike Lewis; Wen-tau Yih; Luke Zettlemoyer; Xi Victoria Lin (Trans. Mach. Learn. Res., 2025)

2 OLMo 2 Furious. - Team OLMo; Pete Walsh; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Shane Arora; Akshita Bhagia; Yuling Gu; Shengyi Huang; Matt Jordan; Nathan Lambert 001; Dustin Schwenk; et al. (CoRR, 2025)

CAT: Content-Adaptive Image Tokenization. - Junhong Shen; Kushal Tirumala; Michihiro Yasunaga; Ishan Misra; Luke Zettlemoyer; Lili Yu; Chunting Zhou (CoRR, 2025)

Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity. - Weixin Liang; Junhong Shen; Genghan Zhang; Ning Dong; Luke Zettlemoyer; Lili Yu (CoRR, 2025)

s1: Simple test-time scaling. - Niklas Muennighoff; Zitong Yang; Weijia Shi; Xiang Lisa Li; Li Fei-Fei 001; Hannaneh Hajishirzi; Luke Zettlemoyer; Percy Liang; Emmanuel J. Candès; Tatsunori Hashimoto (CoRR, 2025)

Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems. - Shangbin Feng; Zifeng Wang 002; Palash Goyal; Yike Wang 002; Weijia Shi; Huang Xia; Hamid Palangi; Luke Zettlemoyer; Yulia Tsvetkov; Chen-Yu Lee; Tomas Pfister (CoRR, 2025)

Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models. - Michihiro Yasunaga; Luke Zettlemoyer; Marjan Ghazvininejad (CoRR, 2025)

(Mis)Fitting: A Survey of Scaling Laws. - Margaret Li; Sneha Kudugunta; Luke Zettlemoyer (CoRR, 2025)

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data. - Tong Chen; Faeze Brahman; Jiacheng Liu 010; Niloofar Mireshghallah; Weijia Shi; Pang Wei Koh; Luke Zettlemoyer; Hannaneh Hajishirzi (CoRR, 2025)

ReasonIR: Training Retrievers for Reasoning Tasks. - Rulin Shao; Rui Qiao 006; Varsha Kishore; Niklas Muennighoff; Xi Victoria Lin; Daniela Rus; Bryan Kian Hsiang Low; Sewon Min; Wen-tau Yih; Pang Wei Koh; Luke Zettlemoyer (CoRR, 2025)

DreamGen: Unlocking Generalization in Robot Learning through Neural Trajectories. - Joel Jang; Seonghyeon Ye; Zongyu Lin; Jiannan Xiang; Johan Bjorck; Yu Fang; Fengyuan Hu; Spencer Huang; Kaushil Kundalia; Yen-Chen Lin; Loic Magne; Ajay Mandlekar; et al. (CoRR, 2025)

OMNIGUARD: An Efficient Approach for AI Safety Moderation Across Modalities. - Sahil Verma; Keegan Hines; Jeff Bilmes; Charlotte Siska; Luke Zettlemoyer; Hila Gonen; Chandan Singh (CoRR, 2025)

High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning. - Tim Franzmeyer; Archie Sravankumar; Lijuan Liu; Yuning Mao; Rui Hou; Sinong Wang; Jakob N. Foerster; Luke Zettlemoyer; Madian Khabsa (CoRR, 2025)

Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models. - Thao Nguyen; Yang Li; Olga Golovneva; Luke Zettlemoyer; Sewoong Oh; Ludwig Schmidt; Xian Li 003 (CoRR, 2025)

Precise Information Control in Long-Form Text Generation. - Jacqueline He; Howard Yen; Margaret Li; Shuyue Stella Li; Zhiyuan Zeng; Weijia Shi; Yulia Tsvetkov; Danqi Chen 001; Pang Wei Koh; Luke Zettlemoyer (CoRR, 2025)

Spurious Rewards: Rethinking Training Signals in RLVR. - Rulin Shao; Shuyue Stella Li; Rui Xin; Scott Geng; Yiping Wang; Sewoong Oh; Simon Shaolei Du; Nathan Lambert 001; Sewon Min; Ranjay Krishna; Yulia Tsvetkov; Hannaneh Hajishirzi; et al. (CoRR, 2025)

FlexOlmo: Open Language Models for Flexible Data Use. - Weijia Shi; Akshita Bhagia; Kevin Farhat; Niklas Muennighoff; Pete Walsh; Jacob Morrison; Dustin Schwenk; Shayne Longpre; Jake Poznanski; Allyson Ettinger; Daogao Liu; Margaret Li; et al. (CoRR, 2025)

Meta CLIP 2: A Worldwide Scaling Recipe. - Yung-Sung Chuang; Yang Li; Dong Wang; Ching-Feng Yeh; Kehan Lyu; Ramya Raghavendra; James Glass 001; Lifei Huang; Jason Weston; Luke Zettlemoyer; Xinlei Chen; Zhuang Liu; et al. (CoRR, 2025)