Towards Semi-Automated Annotation for Prepositional Phrase Attachment. - Sara Rosenthal; William Lipovsky; Kathleen R. McKeown; Kapil Thadani; Jacob Andreas (LREC, 2010)

Corpus Creation for New Genres: A Crowdsourced Approach to PP Attachment. - Mukund Jha; Jacob Andreas; Kapil Thadani; Sara Rosenthal; Kathleen R. McKeown (Mturk@HLT-NAACL, 2010)

Fuzzy Syntactic Reordering for Phrase-based Statistical Machine Translation. - Jacob Andreas; Nizar Habash; Owen Rambow (WMT@EMNLP, 2011)

Semantics-Based Machine Translation with Hyperedge Replacement Grammars. - Bevan K. Jones; Jacob Andreas; Daniel Bauer 002; Karl Moritz Hermann; Kevin Knight (COLING, 2012)

Annotating Agreement and Disagreement in Threaded Discussion. - Jacob Andreas; Sara Rosenthal; Kathleen R. McKeown (LREC, 2012)

The Complexity of Learning Principles and Parameters Grammars - Jacob Andreas (CoRR, 2012)

A Generative Model of Vector Space Semantics. - Jacob Andreas; Zoubin Ghahramani (CVSM@ACL, 2013)

Semantic Parsing as Machine Translation. - Jacob Andreas; Andreas Vlachos 001; Stephen Clark (ACL (2), 2013)

Parsing Graphs with Hyperedge Replacement Grammars. - David Chiang 001; Jacob Andreas; Daniel Bauer 002; Karl Moritz Hermann; Bevan K. Jones; Kevin Knight (ACL (1), 2013)

How much do word embeddings encode about syntax? - Jacob Andreas; Dan Klein 001 (ACL (2), 2014)

Grounding Language with Points and Paths in Continuous Spaces. - Jacob Andreas; Dan Klein 001 (CoNLL, 2014)

Unsupervised Transcription of Piano Music. - Taylor Berg-Kirkpatrick; Jacob Andreas; Dan Klein 001 (NIPS, 2014)

Alignment-Based Compositional Semantics for Instruction Following. - Jacob Andreas; Dan Klein 001 (EMNLP, 2015)

When and why are log-linear models self-normalizing? - Jacob Andreas; Dan Klein 001 (HLT-NAACL, 2015)

On the Accuracy of Self-Normalized Log-Linear Models. - Jacob Andreas; Maxim Rabinovich; Michael I. Jordan; Dan Klein 001 (NIPS, 2015)

Deep Compositional Question Answering with Neural Module Networks. - Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Dan Klein 001 (CoRR, 2015)

Neural Module Networks. - Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Dan Klein 001 (CVPR, 2016)

Reasoning about Pragmatics with Neural Listeners and Speakers. - Jacob Andreas; Dan Klein 001 (EMNLP, 2016)

Learning to Compose Neural Networks for Question Answering. - Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Dan Klein 001 (HLT-NAACL, 2016)

Translating Neuralese. - Jacob Andreas; Anca D. Dragan; Dan Klein 001 (ACL (1), 2017)

A Minimal Span-Based Neural Constituency Parser. - Mitchell Stern; Jacob Andreas; Dan Klein 001 (ACL (1), 2017)

Modeling Relationships in Referential Expressions with Compositional Modular Networks. - Ronghang Hu; Marcus Rohrbach; Jacob Andreas; Trevor Darrell; Kate Saenko (CVPR, 2017)

Analogs of Linguistic Structure in Deep Representations. - Jacob Andreas; Dan Klein 001 (EMNLP, 2017)

Learning to Reason: End-to-End Module Networks for Visual Question Answering. - Ronghang Hu; Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Kate Saenko (ICCV, 2017)

Modular Multitask Reinforcement Learning with Policy Sketches. - Jacob Andreas; Dan Klein 001; Sergey Levine (ICML, 2017)

Explainable Neural Computation via Stack Neural Module Networks. - Ronghang Hu; Jacob Andreas; Trevor Darrell; Kate Saenko (ECCV (7), 2018)

Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? - Maithra Raghu; Alex Irpan; Jacob Andreas; Robert Kleinberg; Quoc V. Le; Jon M. Kleinberg (ICML, 2018)

Learning with Latent Language. - Jacob Andreas; Dan Klein 001; Sergey Levine (NAACL-HLT, 2018)

Unified Pragmatic Models for Generating and Following Instructions. - Daniel Fried; Jacob Andreas; Dan Klein 001 (NAACL-HLT, 2018)

Speaker-Follower Models for Vision-and-Language Navigation. - Daniel Fried; Ronghang Hu; Volkan Cirik; Anna Rohrbach; Jacob Andreas; Louis-Philippe Morency; Taylor Berg-Kirkpatrick; Kate Saenko; Dan Klein 001; Trevor Darrell (NeurIPS, 2018)

Learning from Language. - Jacob Andreas (2018)

Measuring Compositionality in Representation Learning. - Jacob Andreas (ICLR (Poster), 2019)

Guiding Policies with Language via Meta-Learning. - John D. Co-Reyes; Abhishek Gupta 004; Suvansh Sanjeev; Nick Altieri 001; Jacob Andreas; John DeNero; Pieter Abbeel; Sergey Levine (ICLR (Poster), 2019)

A Survey of Reinforcement Learning Informed by Natural Language. - Jelena Luketina; Nantas Nardelli; Gregory Farquhar; Jakob N. Foerster; Jacob Andreas; Edward Grefenstette; Shimon Whiteson; Tim Rocktäschel (IJCAI, 2019)

Pragmatically Informative Text Generation. - Sheng Shen 001; Daniel Fried; Jacob Andreas; Dan Klein 001 (NAACL-HLT (1), 2019)

Good-Enough Compositional Data Augmentation. - Jacob Andreas (ACL, 2020)

Experience Grounds Language. - Yonatan Bisk; Ari Holtzman; Jesse Thomason; Jacob Andreas; Yoshua Bengio; Joyce Chai; Mirella Lapata; Angeliki Lazaridou; Jonathan May; Aleksandr Nisnevich; Nicolas Pinto; Joseph P. Turian (EMNLP (1), 2020)

Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment. - Geeticka Chauhan; Ruizhi Liao 001; William M. Wells III; Jacob Andreas; Xin Wang; Seth J. Berkowitz; Steven Horng; Peter Szolovits; Polina Golland (MICCAI (2), 2020)

Compositional Explanations of Neurons. - Jesse Mu; Jacob Andreas (NeurIPS, 2020)

A Benchmark for Systematic Generalization in Grounded Language Understanding. - Laura Ruis; Jacob Andreas; Marco Baroni; Diane Bouchacourt; Brenden M. Lake (NeurIPS, 2020)

Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data. - Alana Marzoev; Samuel Madden 001; M. Frans Kaashoek; Michael J. Cafarella; Jacob Andreas (CoRR, 2020)

Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction. - Eric Chu; Deb Roy; Jacob Andreas (CoRR, 2020)

Task-Oriented Dialogue as Dataflow Synthesis. - Jacob Andreas; John Bufe; David Burkett; Charles Chen; Josh Clausman; Jean Crawford; Kate Crim; Jordan DeLoach; Leah Dorner; Jason Eisner; Hao Fang 002; Alan Guo; et al. (Trans. Assoc. Comput. Linguistics, 2020)

Lexicon Learning for Few Shot Sequence Modeling. - Ekin Akyürek; Jacob Andreas (ACL/IJCNLP (1), 2021)

Implicit Representations of Meaning in Neural Language Models. - Belinda Z. Li; Maxwell I. Nye; Jacob Andreas (ACL/IJCNLP (1), 2021)

What Context Features Can Transformer Language Models Use? - Joe O'Connor; Jacob Andreas (ACL/IJCNLP (1), 2021)

Value-Agnostic Conversational Semantic Parsing. - Emmanouil Antonios Platanios; Adam Pauls; Subhro Roy; Yuchen Zhang 002; Alexander Kyte; Alan Guo; Sam Thomson; Jayant Krishnamurthy; Jason Andrew Wolfe; Jacob Andreas; Dan Klein 001 (ACL/IJCNLP (1), 2021)

Language as a bootstrap for compositional visual reasoning. - Catherine Wong; Yoni Friedman; Jacob Andreas; Josh Tenenbaum 001 (CogSci, 2021)

The Low-Dimensional Linear Geometry of Contextualized Word Representations. - Evan Hernandez; Jacob Andreas (CoNLL, 2021)

How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction. - D. Anthony Bau; Jacob Andreas (EMNLP (1), 2021)

Toward a Visual Concept Vocabulary for GAN Latent Space. - Sarah Schwettmann; Evan Hernandez; David Bau; Samuel Klein; Jacob Andreas; Antonio Torralba 001 (ICCV, 2021)

Learning to Recombine and Resample Data For Compositional Generalization. - Ekin Akyürek; Afra Feyza Akyürek; Jacob Andreas (ICLR, 2021)

Representing Partial Programs with Blended Abstract Semantics. - Maxwell I. Nye; Yewen Pu; Matthew Bowers; Jacob Andreas; Joshua B. Tenenbaum; Armando Solar-Lezama (ICLR, 2021)

Leveraging Language to Learn Program Abstractions and Search Heuristics. - Catherine Wong; Kevin Ellis; Joshua B. Tenenbaum; Jacob Andreas (ICML, 2021)

Multitasking Inhibits Semantic Drift. - Athul Paul Jacob; Mike Lewis; Jacob Andreas (NAACL-HLT, 2021)

Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention. - Pengcheng Yin; Hao Fang 002; Graham Neubig; Adam Pauls; Emmanouil Antonios Platanios; Yu Su 001; Sam Thomson; Jacob Andreas (NAACL-HLT, 2021)

Teachable Reinforcement Learning via Advice Distillation. - Olivia Watkins; Abhishek Gupta 004; Trevor Darrell; Pieter Abbeel; Jacob Andreas (NeurIPS, 2021)

Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales. - Jacob Andreas; Gasper Begus; Michael M. Bronstein; Roee Diamant; Denley Delaney; Shane Gero; Shafi Goldwasser; David F. Gruber; Sarah de Haas; Peter Malkin; Roger Payne; Giovanni Petri; et al. (CoRR, 2021)

Lexicon Learning for Few-Shot Neural Sequence Modeling. - Ekin Akyürek; Jacob Andreas (CoRR, 2021)

FairyTailor: A Multimodal Generative Framework for Storytelling. - Eden Bensaid; Mauro Martino; Benjamin Hoover; Jacob Andreas; Hendrik Strobelt (CoRR, 2021)

How Do Neural Sequence Models Generalize? Local and Global Context Cues for Out-of-Distribution Prediction. - D. Anthony Bau; Jacob Andreas (CoRR, 2021)

Modeling Strong and Human-Like Gameplay with KL-Regularized Search. - Athul Paul Jacob; David J. Wu 002; Gabriele Farina; Adam Lerer; Anton Bakhtin; Jacob Andreas; Noam Brown (CoRR, 2021)

Guided K-best Selection for Semantic Parsing Annotation. - Anton Belyy; Chieh-Yang Huang; Jacob Andreas; Emmanouil Antonios Platanios; Sam Thomson; Richard Shin; Subhro Roy; Aleksandr Nisnevich; Charles Chen; Benjamin Van Durme (ACL (demo), 2022)

Skill Induction and Planning with Latent Language. - Pratyusha Sharma; Antonio Torralba 001; Jacob Andreas (ACL (1), 2022)

Identifying concept libraries from language about object structure. - Catherine Wong; William P. McCarthy; Gabriel Grand; Yoni Friedman; Josh Tenenbaum 001; Jacob Andreas; Robert D. Hawkins; Judith E. Fan (CogSci, 2022)

Towards Tracing Knowledge in Language Models Back to the Training Data. - Ekin Akyürek; Tolga Bolukbasi; Frederick Liu; Binbin Xiong; Ian Tenney; Jacob Andreas; Kelvin Guu (EMNLP (Findings), 2022)

Language Models as Agent Models. - Jacob Andreas (EMNLP (Findings), 2022)

Hierarchical Phrase-Based Sequence-to-Sequence Learning. - Bailin Wang; Ivan Titov 001; Jacob Andreas; Yoon Kim (EMNLP, 2022)

Subspace Regularizers for Few-Shot Class Incremental Learning. - Afra Feyza Akyürek; Ekin Akyürek; Derry Wijaya; Jacob Andreas (ICLR, 2022)

Natural Language Descriptions of Deep Visual Features. - Evan Hernandez; Sarah Schwettmann; David Bau; Teona Bagashvili; Antonio Torralba 001; Jacob Andreas (ICLR, 2022)

Modeling Strong and Human-Like Gameplay with KL-Regularized Search. - Athul Paul Jacob; David J. Wu 002; Gabriele Farina; Adam Lerer; Hengyuan Hu; Anton Bakhtin; Jacob Andreas; Noam Brown (ICML, 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)

Pre-Trained Language Models for Interactive Decision-Making. - Shuang Li 013; Xavier Puig; Chris Paxton 001; Yilun Du; Clinton Wang; Linxi Fan; Tao Chen 046; De-An Huang; Ekin Akyürek; Anima Anandkumar; Jacob Andreas; Igor Mordatch; et al. (NeurIPS, 2022)

Correcting Robot Plans with Natural Language Feedback. - Pratyusha Sharma; Balakumar Sundaralingam; Valts Blukis; Chris Paxton 001; Tucker Hermans; Antonio Torralba 001; Jacob Andreas; Dieter Fox (Robotics: Science and Systems, 2022)

Compositionality as Lexical Symmetry. - Ekin Akyürek; Jacob Andreas (CoRR, 2022)

Tracing Knowledge in Language Models Back to the Training Data. - Ekin Akyürek; Tolga Bolukbasi; Frederick Liu; Binbin Xiong; Ian Tenney; Jacob Andreas; Kelvin Guu (CoRR, 2022)

ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications. - Alex Gu; Tamara Mitrovska; Daniela Velez; Jacob Andreas; Armando Solar-Lezama (CoRR, 2022)

LexSym: Compositionality as Lexical Symmetry. - Ekin Akyürek; Jacob Andreas (ACL (1), 2023)

The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding. - Hao Fang 002; Anusha Balakrishnan; Harsh Jhamtani; John Bufe; Jean Crawford; Jayant Krishnamurthy; Adam Pauls; Jason Eisner; Jacob Andreas; Dan Klein 001 (ACL (Findings), 2023)

Language Modeling with Latent Situations. - Belinda Z. Li; Maxwell I. Nye; Jacob Andreas (ACL (Findings), 2023)

Grokking of Hierarchical Structure in Vanilla Transformers. - Shikhar Murty; Pratyusha Sharma; Jacob Andreas; Christopher D. Manning (ACL (2), 2023)

Alignment via Mutual Information. - Shinjini Ghosh; Yoon Kim; Ramón Fernandez Astudillo; Tahira Naseem; Jacob Andreas (CoNLL, 2023)

Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? - Kevin Liu; Stephen Casper; Dylan Hadfield-Menell; Jacob Andreas (EMNLP, 2023)

Pushdown Layers: Encoding Recursive Structure in Transformer Language Models. - Shikhar Murty; Pratyusha Sharma; Jacob Andreas; Christopher D. Manning (EMNLP, 2023)

What learning algorithm is in-context learning? Investigations with linear models. - Ekin Akyürek; Dale Schuurmans; Jacob Andreas; Tengyu Ma 001; Denny Zhou (ICLR, 2023)

Characterizing intrinsic compositionality in transformers with Tree Projections. - Shikhar Murty; Pratyusha Sharma; Jacob Andreas; Christopher D. Manning (ICLR, 2023)

Guiding Pretraining in Reinforcement Learning with Large Language Models. - Yuqing Du; Olivia Watkins; Zihan Wang; Cédric Colas; Trevor Darrell; Pieter Abbeel; Abhishek Gupta 004; Jacob Andreas (ICML, 2023)

PromptBoosting: Black-Box Text Classification with Ten Forward Passes. - Bairu Hou; Joe O'Connor; Jacob Andreas; Shiyu Chang; Yang Zhang 001 (ICML, 2023)

FIND: A Function Description Benchmark for Evaluating Interpretability Methods. - Sarah Schwettmann; Tamar Rott Shaham; Joanna Materzynska; Neil Chowdhury; Shuang Li 013; Jacob Andreas; David Bau; Antonio Torralba 001 (NeurIPS, 2023)

The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. - Ziqian Zhong; Ziming Liu; Max Tegmark; Jacob Andreas (NeurIPS, 2023)

LaMPP: Language Models as Probabilistic Priors for Perception and Action. - Belinda Z. Li; William Chen; Pratyusha Sharma; Jacob Andreas (CoRR, 2023)

Language Models Trained on Media Diets Can Predict Public Opinion. - Eric Chu; Jacob Andreas; Stephen Ansolabehere; Deb Roy (CoRR, 2023)

Measuring and Manipulating Knowledge Representations in Language Models. - Evan Hernandez; Belinda Z. Li; Jacob Andreas (CoRR, 2023)

From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought. - Lionel Wong; Gabriel Grand; Alexander K. Lew; Noah D. Goodman; Vikash K. Mansinghka; Jacob Andreas; Joshua B. Tenenbaum (CoRR, 2023)

A Function Interpretation Benchmark for Evaluating Interpretability Methods. - Sarah Schwettmann; Tamar Rott Shaham; Joanna Materzynska; Neil Chowdhury; Shuang Li 013; Jacob Andreas; David Bau; Antonio Torralba 001 (CoRR, 2023)

Evaluating the Utility of Model Explanations for Model Development. - Shawn Im; Jacob Andreas; Yilun Zhou (CoRR, 2023)

Learning adaptive planning representations with natural language guidance. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (CoRR, 2023)

Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. - Afra Feyza Akyürek; Ekin Akyürek; Leshem Choshen; Derry Wijaya; Jacob Andreas (ACL (Findings), 2024)

Toward In-Context Teaching: Adapting Examples to Students' Misconceptions. - Alexis Ross; Jacob Andreas (ACL (1), 2024)

Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. - Chengxu Zhuang; Evelina Fedorenko; Jacob Andreas (ACL (Findings), 2024)

Adaptive Language-Guided Abstraction from Contrastive Explanations. - Andi Peng; Belinda Z. Li; Ilia Sucholutsky; Nishanth Kumar; Julie Shah; Jacob Andreas; Andreea Bobu (CoRL, 2024)

Language-to-Code Translation with a Single Labeled Example. - Kaj Bostrom; Harsh Jhamtani; Hao Fang 002; Sam Thomson; Richard Shin; Patrick Xia 002; Benjamin Van Durme; Jason Eisner; Jacob Andreas (EMNLP, 2024)

MisinfoEval: Generative AI in the Era of "Alternative Facts". - Saadia Gabriel; Liang Lyu; James Siderius; Marzyeh Ghassemi; Jacob Andreas; Asuman E. Ozdaglar (EMNLP, 2024)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code. - Gabriel Grand; Lionel Wong; Matthew Bowers; Theo X. Olausson; Muxin Liu; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

Linearity of Relation Decoding in Transformer Language Models. - Evan Hernandez; Arnab Sen Sharma; Tal Haklay; Kevin Meng; Martin Wattenberg; Jacob Andreas; Yonatan Belinkov; David Bau (ICLR, 2024)

Modeling Boundedly Rational Agents with Latent Inference Budgets. - Athul Paul Jacob; Abhishek Gupta 004; Jacob Andreas (ICLR, 2024)

The Consensus Game: Language Model Generation via Equilibrium Search. - Athul Paul Jacob; Yikang Shen; Gabriele Farina; Jacob Andreas (ICLR, 2024)

Learning with Language-Guided State Abstractions. - Andi Peng; Ilia Sucholutsky; Belinda Z. Li; Theodore R. Sumers; Thomas L. Griffiths 001; Jacob Andreas; Julie Shah (ICLR, 2024)

Learning Grounded Action Abstractions from Language. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

In-Context Language Learning: Architectures and Algorithms. - Ekin Akyürek; Bailin Wang; Yoon Kim; Jacob Andreas (ICML, 2024)

Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. - Bairu Hou; Yujian Liu; Kaizhi Qian; Jacob Andreas; Shiyu Chang; Yang Zhang 001 (ICML, 2024)

A Multimodal Automated Interpretability Agent. - Tamar Rott Shaham; Sarah Schwettmann; Franklin Wang; Achyuta Rajaram; Evan Hernandez; Jacob Andreas; Antonio Torralba 001 (ICML, 2024)

Natural Language Decomposition and Interpretation of Complex Utterances. - Harsh Jhamtani; Hao Fang 002; Patrick Xia 002; Eran Levy; Jacob Andreas; Benjamin Van Durme (IJCAI, 2024)

Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning. - Athul Paul Jacob; Gabriele Farina; Jacob Andreas (NAACL-HLT, 2024)

Interpreting User Requests in the Context of Natural Language Standing Instructions. - Nikita Moghe; Patrick Xia 002; Jacob Andreas; Jason Eisner; Benjamin Van Durme; Harsh Jhamtani (NAACL-HLT (Findings), 2024)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks. - Zhaofeng Wu; Linlu Qiu; Alexis Ross; Ekin Akyürek; Boyuan Chen 003; Bailin Wang; Najoung Kim; Jacob Andreas; Yoon Kim (NAACL-HLT, 2024)

Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. - Chengxu Zhuang; Evelina Fedorenko; Jacob Andreas (NAACL-HLT, 2024)

Algorithmic Capabilities of Random Transformers. - Ziqian Zhong; Jacob Andreas (NeurIPS, 2024)

Loose LIPS Sink Ships: Asking Questions in Battleship with Language-Informed Program Sampling. - Gabriel Grand; Valerio Pepe; Jacob Andreas; Joshua B. Tenenbaum (CoRR, 2024)

Bayesian Preference Elicitation with Language Models. - Kunal Handa; Yarin Gal; Ellie Pavlick; Noah D. Goodman; Jacob Andreas; Alex Tamkin; Belinda Z. Li (CoRR, 2024)

An Incomplete Loop: Deductive, Inductive, and Abductive Learning in Large Language Models. - Emmy Liu; Graham Neubig; Jacob Andreas (CoRR, 2024)

Automatic Discovery of Visual Circuits. - Achyuta Rajaram; Neil Chowdhury; Antonio Torralba 001; Jacob Andreas; Sarah Schwettmann (CoRR, 2024)

Policy Learning with a Language Bottleneck. - Megha Srivastava; Cédric Colas; Dorsa Sadigh; Jacob Andreas (CoRR, 2024)

Learning Phonotactics from Linguistic Informants. - Canaan Breiss; Alexis Ross; Amani Maina-Kilaas; Roger Levy; Jacob Andreas (CoRR, 2024)

Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models. - Anna A. Ivanova; Aalok Sathe; Benjamin Lipkin; Unnathi Kumar; Setayesh Radkani; Thomas Hikaru Clark; Carina Kauf; Jennifer Hu 001; R. T. Pramod; Gabriel Grand; Vivian C. Paulun; Maria Ryskina; et al. (CoRR, 2024)

A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation. - Bairu Hou; Yang Zhang 001; Jacob Andreas; Shiyu Chang (CoRR, 2024)

Unforgettable Generalization in Language Models. - Eric Zhang; Leshem Choshen; Jacob Andreas (CoRR, 2024)

Learning Linear Attention in Polynomial Time. - Morris Yau; Ekin Akyürek; Jiayuan Mao; Joshua B. Tenenbaum; Stefanie Jegelka; Jacob Andreas (CoRR, 2024)

A Hitchhiker's Guide to Scaling Law Estimation. - Leshem Choshen; Yang Zhang; Jacob Andreas (CoRR, 2024)

LoRA vs Full Fine-tuning: An Illusion of Equivalence. - Reece Shuttleworth; Jacob Andreas; Antonio Torralba 001; Pratyusha Sharma (CoRR, 2024)

The Surprising Effectiveness of Test-Time Training for Abstract Reasoning. - Ekin Akyürek; Mehul Damani; Linlu Qiu; Han Guo; Yoon Kim; Jacob Andreas (CoRR, 2024)

Decision-Oriented Dialogue for Human-AI Collaboration. - Jessy Lin; Nicholas Tomlin; Jacob Andreas; Jason Eisner (Trans. Assoc. Comput. Linguistics, 2024)

LLM Agents for Coordinating Multi-User Information Gathering. - Harsh Jhamtani; Jacob Andreas; Benjamin Van Durme (ACL (Findings), 2025)

Learning How Hard to Think: Input-Adaptive Allocation of LM Computation. - Mehul Damani; Idan Shenfeld; Andi Peng; Andreea Bobu; Jacob Andreas (ICLR, 2025)

Eliciting Human Preferences with Language Models. - Belinda Z. Li; Alex Tamkin; Noah D. Goodman; Jacob Andreas (ICLR, 2025)

A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation. - Bairu Hou; Yang Zhang; Jacob Andreas; Shiyu Chang (NAACL (Long Papers), 2025)

Language Modeling with Editable External Knowledge. - Belinda Z. Li; Emmy Liu; Alexis Ross; Abbas Zeitoun; Graham Neubig; Jacob Andreas (NAACL (Findings), 2025)

LM Agents for Coordinating Multi-User Information Gathering. - Harsh Jhamtani; Jacob Andreas; Benjamin Van Durme (CoRR, 2025)

(How) Do Language Models Track State? - Belinda Z. Li; Zifan Carl Guo; Jacob Andreas (CoRR, 2025)

ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning. - Bairu Hou; Yang Zhang 001; Jiabao Ji; Yujian Liu; Kaizhi Qian; Jacob Andreas; Shiyu Chang (CoRR, 2025)

Self-Steering Language Models. - Gabriel Grand; Joshua B. Tenenbaum; Vikash K. Mansinghka; Alexander K. Lew; Jacob Andreas (CoRR, 2025)

Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation. - Peter Baile Chen; Yi Zhang 001; Dan Roth 001; Samuel Madden 001; Jacob Andreas; Michael J. Cafarella (CoRR, 2025)

Breakpoint: Scalable evaluation of system-level reasoning in LLM code agents. - Kaivalya Hariharan; Uzay Girit; Atticus Wang; Jacob Andreas (CoRR, 2025)

Line of Sight: On Linear Representations in VLLMs. - Achyuta Rajaram; Sarah Schwettmann; Jacob Andreas; Arthur Conmy (CoRR, 2025)

Sequential-Parallel Duality in Prefix Scannable Models. - Morris Yau; Sharut Gupta; Valerie Engelmayer; Kazuki Irie; Stefanie Jegelka; Jacob Andreas (CoRR, 2025)

Can Gradient Descent Simulate Prompting? - Eric Zhang; Leshem Choshen; Jacob Andreas (CoRR, 2025)

LLM Hypnosis: Exploiting User Feedback for Unauthorized Knowledge Injection to All Users. - Almog Hilel; Idan Shenfeld; Jacob Andreas; Leshem Choshen (CoRR, 2025)

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models. - Lionel Wong; Katherine M. Collins; Lance Ying; Cedegao E. Zhang; Adrian Weller; Tobias Gerstenberg; Timothy O'Donnell; Alexander K. Lew; Jacob Andreas; Joshua B. Tenenbaum; Tyler Brooke-Wilson (CoRR, 2025)

Assessing Adaptive World Models in Machines with Novel Games. - Lance Ying; Katherine M. Collins; Prafull Sharma; Cedric Colas; Kaiya Ivy Zhao; Adrian Weller; Zenna Tavares; Phillip Isola; Samuel J. Gershman; Jacob Andreas; Thomas L. Griffiths 001; François Chollet; et al. (CoRR, 2025)

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty. - Mehul Damani; Isha Puri; Stewart Slocum; Idan Shenfeld; Leshem Choshen; Yoon Kim; Jacob Andreas (CoRR, 2025)