HMDB: the Human Metabolome Database. - David S. Wishart; Dan Tzur; Craig Knox; Roman Eisner; Anchi Guo; Nelson Young; Dean Cheng; Kevin Jewell; David Arndt; Summit Sawhney; Chris Fung; Lisa Nikolai; et al. (Nucleic Acids Res., 2007)

Unsupervised Induction of Cross-Lingual Semantic Relations. - Mike Lewis; Mark Steedman (EMNLP, 2013)

Grounded spatial symbols for task planning based on experience. - Kai Welke; Peter Kaiser 001; Alexey Kozlov; Nils Adermann; Tamim Asfour; Mike Lewis; Mark Steedman (Humanoids, 2013)

Migrating To The Cloud: Lessons And Limitations Of 'Traditional' IS Success Models. - Imran Khan Azeemi; Mike Lewis; Theo Tryfonas (CSER, 2013)

Combined Distributional and Logical Semantics. - Mike Lewis; Mark Steedman (Trans. Assoc. Comput. Linguistics, 2013)

A* CCG Parsing with a Supertag-factored Model. - Mike Lewis; Mark Steedman (EMNLP, 2014)

Extracting common sense knowledge from text for robot planning. - Peter Kaiser 001; Mike Lewis; Ronald P. A. Petrick; Tamim Asfour; Mark Steedman (ICRA, 2014)

Improved CCG Parsing with Semi-supervised Supertagging. - Mike Lewis; Mark Steedman (Trans. Assoc. Comput. Linguistics, 2014)

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

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

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

A Corpus of Natural Language for Visual Reasoning. - Alane Suhr; Mike Lewis; James Yeh; Yoav Artzi (ACL (2), 2017)

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

Deal or No Deal? End-to-End Learning of Negotiation Dialogues. - Mike Lewis; Denis Yarats; Yann N. Dauphin; Devi Parikh; Dhruv Batra (EMNLP, 2017)

Hierarchical Neural Story Generation. - Angela Fan; Mike Lewis; Yann N. Dauphin (ACL (1), 2018)

A Dataset for Telling the Stories of Social Media Videos. - Spandana Gella; Mike Lewis; Marcus Rohrbach (EMNLP, 2018)

Neural Compositional Denotational Semantics for Question Answering. - Nitish Gupta; Mike Lewis (EMNLP, 2018)

Semantic Parsing for Task Oriented Dialog using Hierarchical Representations. - Sonal Gupta; Rushin Shah; Mrinal Mohit; Anuj Kumar; Mike Lewis (EMNLP, 2018)

Hierarchical Text Generation and Planning for Strategic Dialogue. - Denis Yarats; Mike Lewis (ICML, 2018)

Common ground control system (CGCS) to support autonomous object observation, collection, and response in multi-domain environments. - Paul C. Hershey; Mike Sica; Mike Lewis (SysCon, 2018)

Evaluating Visual Reasoning through Grounded Language Understanding. - Alane Suhr; Mike Lewis; James Yeh; Yoav Artzi (AI Mag., 2018)

Strategies for Structuring Story Generation. - Angela Fan; Mike Lewis; Yann N. Dauphin (ACL (1), 2019)

Community Regularization of Visually-Grounded Dialog. - Akshat Agarwal; Swaminathan Gurumurthy; Vasu Sharma; Mike Lewis; Katia P. Sycara (AAMAS, 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)

Generative Question Answering: Learning to Answer the Whole Question. - Mike Lewis; Angela Fan (ICLR (Poster), 2019)

Cross-lingual Transfer Learning for Multilingual Task Oriented Dialog. - Sebastian Schuster; Sonal Gupta; Rushin Shah; Mike Lewis (NAACL-HLT (1), 2019)

Hierarchical Decision Making by Generating and Following Natural Language Instructions. - Hengyuan Hu; Denis Yarats; Qucheng Gong; Yuandong Tian; Mike Lewis (NeurIPS, 2019)

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

MelNet: A Generative Model for Audio in the Frequency Domain. - Sean Vasquez; Mike Lewis (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)

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

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)

Asking and Answering Questions to Evaluate the Factual Consistency of Summaries. - Alex Wang; Kyunghyun Cho; Mike Lewis (ACL, 2020)

Conversational Semantic Parsing. - Armen Aghajanyan; Jean Maillard; Akshat Shrivastava; Keith Diedrick; Michael Haeger; Haoran Li 007; Yashar Mehdad; Veselin Stoyanov; Anuj Kumar; Mike Lewis; Sonal Gupta (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)

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

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. - Patrick Lewis 001; Ethan Perez; Aleksandra Piktus; Fabio Petroni; Vladimir Karpukhin; Naman Goyal 001; Heinrich Küttler; Mike Lewis; Wen-tau Yih; Tim Rocktäschel; Sebastian Riedel 001; Douwe Kiela (NeurIPS, 2020)

Conversational Semantic Parsing. - Armen Aghajanyan; Jean Maillard; Akshat Shrivastava; Keith Diedrick; Mike Haeger; Haoran Li 007; Yashar Mehdad; Ves Stoyanov; Anuj Kumar; Mike Lewis; Sonal Gupta (CoRR, 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)

Shortformer: Better Language Modeling using Shorter Inputs. - Ofir Press; Noah A. Smith; Mike Lewis (ACL/IJCNLP (1), 2021)

Joint Verification and Reranking for Open Fact Checking Over Tables. - Michael Sejr Schlichtkrull; Vladimir Karpukhin; Barlas Oguz; Mike Lewis; Wen-tau Yih; Sebastian Riedel 001 (ACL/IJCNLP (1), 2021)

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

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

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

Sparse Distillation: Speeding Up Text Classification by Using Bigger Models. - Qinyuan Ye; Madian Khabsa; Mike Lewis; Sinong Wang; Xiang Ren 001; Aaron Jaech (CoRR, 2021)

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

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

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)

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)

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. - Ofir Press; Noah A. Smith; Mike Lewis (ICLR, 2022)

Tricks for Training Sparse Translation Models. - Dheeru Dua; Shruti Bhosale; Vedanuj Goswami; James Cross 003; Mike Lewis; Angela Fan (NAACL-HLT, 2022)

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

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

Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models. - Qinyuan Ye; Madian Khabsa; Mike Lewis; Sinong Wang; Xiang Ren 001; Aaron Jaech (NAACL-HLT, 2022)

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

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

AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies. - Weiyan Shi; Emily Dinan; Adi Renduchintala; Daniel Fried; Athul Paul Jacob; Zhou Yu; Mike Lewis (CoRR, 2022)

Improving Chess Commentaries by Combining Language Models with Symbolic Reasoning Engines. - Andrew Lee 001; David Wu; Emily Dinan; Mike Lewis (CoRR, 2022)

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

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

Residual Prompt Tuning: improving prompt tuning with residual reparameterization. - Anastasia Razdaibiedina; Yuning Mao; Madian Khabsa; Mike Lewis; Rui Hou; Jimmy Ba; Amjad Almahairi (ACL (Findings), 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)

Measuring and Narrowing the Compositionality Gap in Language Models. - Ofir Press; Muru Zhang; Sewon Min; Ludwig Schmidt; Noah A. Smith; Mike Lewis (EMNLP (Findings), 2023)

AutoReply: Detecting Nonsense in Dialogue with Discriminative Replies. - Weiyan Shi; Emily Dinan; Adi Renduchintala; Daniel Fried; Athul Paul Jacob; Zhou Yu; Mike Lewis (EMNLP (Findings), 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)

Progressive Prompts: Continual Learning for Language Models. - Anastasia Razdaibiedina; Yuning Mao; Rui Hou; Madian Khabsa; Mike Lewis; Amjad Almahairi (ICLR, 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)

Coder Reviewer Reranking for Code Generation. - Tianyi Zhang; Tao Yu 009; Tatsunori Hashimoto; Mike Lewis; Wen-Tau Yih; Daniel Fried; Sida Wang 001 (ICML, 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)

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)

Contrastive Decoding Improves Reasoning in Large Language Models. - Sean O'Brien; Mike Lewis (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)

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)

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)

Efficient Streaming Language Models with Attention Sinks. - Guangxuan Xiao; Yuandong Tian; Beidi Chen; Song Han 003; 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)

Effective Long-Context Scaling of Foundation Models. - Wenhan Xiong; Jingyu Liu; Igor Molybog; Hejia Zhang; Prajjwal Bhargava; Rui Hou; Louis Martin; Rashi Rungta; Karthik Abinav Sankararaman; Barlas Oguz; Madian Khabsa; Han Fang; et al. (NAACL-HLT, 2024)

Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training. - Zexuan Zhong; Mengzhou Xia; Danqi Chen 001; Mike Lewis (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)

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)

Compute Optimal Scaling of Skills: Knowledge vs Reasoning. - Nicholas Roberts; Niladri S. Chatterji; Sharan Narang; Mike Lewis; Dieuwke Hupkes (ACL (Findings), 2025)

Law of the Weakest Link: Cross Capabilities of Large Language Models. - Ming Zhong 005; Aston Zhang; Xuewei Wang; Rui Hou; Wenhan Xiong; Chenguang Zhu 001; Zhengxing Chen; Liang Tan; Chloe Bi; Mike Lewis; Sravya Popuri; Sharan Narang; et al. (ICLR, 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)

Optimizing Pretraining Data Mixtures with LLM-Estimated Utility. - William Held; Bhargavi Paranjape; Punit Singh Koura; Mike Lewis; Frank Zhang; Todor Mihaylov (CoRR, 2025)

BTS: Harmonizing Specialized Experts into a Generalist LLM. - Qizhen Zhang 002; Prajjwal Bhargava; Chloe Bi; Chris X. Cai; Jakob N. Foerster; Jeremy Fu; Punit Singh Koura; Ruan Silva; Sheng Shen 016; Emily Dinan; Suchin Gururangan; Mike Lewis (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)