Lewis, Mike

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019) · arXiv

Digital Humanities and ScholarshipComputational and Text Analysis Methods

Cited by 16,515

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 8,821

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8,816

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-T., Rocktäschel, T., et al. (2020) · arXiv

Safety Systems Engineering in AutonomyEthics and Social Impacts of AI

Cited by 3,101

Hierarchical Neural Story Generation

Fan, A., Lewis, M., & Dauphin, Y. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingArtificial Intelligence in Games

Cited by 1,266

Hierarchical Neural Story Generation

Fan, A., Lewis, M., & Dauphin, Y. (2018) · arXiv

Topic ModelingArtificial Intelligence in Games

Cited by 1,242

End-to-end Neural Coreference Resolution

Lee, K., He, L., Lewis, M., & Zettlemoyer, L. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 869

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Min, S., Krishna, K., Lyu, X., Lewis, M., Yih, W.-T., Koh, P., Iyyer, M., Zettlemoyer, L., & Hajishirzi, H. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 407

Asking and Answering Questions to Evaluate the Factual Consistency of Summaries

Wang, A., Cho, K., & Lewis, M. (2020) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 356

Deal or No Deal? End-to-End Learning of Negotiation Dialogues

Lewis, M., Yarats, D., Dauphin, Y., Parikh, D., & Batra, D. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Speech and dialogue systemsMulti-Agent Systems and Negotiation

Cited by 347

Generalization through Memorization: Nearest Neighbor Language Models

Khandelwal, U., Levy, O., Jurafsky, D., Zettlemoyer, L., & Lewis, M. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 285

Human-level play in the game of Diplomacy by combining language models with strategic reasoning

Meta Fundamental AI Research Diplomacy Team (FAIR)†, Bakhtin, A., Brown, N., Dinan, E., Farina, G., Flaherty, C., Fried, D., Goff, A., Gray, J., Hu, H., et al. (2022) · Science

Artificial Intelligence in GamesSpeech and dialogue systems

Cited by 241

REPLUG: Retrieval-Augmented Black-Box Language Models

Shi, W., Min, S., Yasunaga, M., Seo, M., James, R., Lewis, M., Zettlemoyer, L., & Yih, W.-T. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 209

MetaICL: Learning to Learn In Context

Min, S., Lewis, M., Zettlemoyer, L., & Hajishirzi, H. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 169

Nearest Neighbor Machine Translation

Khandelwal, U., Fan, A., Jurafsky, D., Zettlemoyer, L., & Lewis, M. (2020) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 165

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Press, O., Smith, N. A., & Lewis, M. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 161

MelNet: a generative model for audio in the frequency domain

Vasquez, S., & Lewis, M. (2019) · arXiv

Speech Recognition and SynthesisMusic and Audio Processing

Cited by 107

BASE Layers: Simplifying Training of Large, Sparse Models

Lewis, M., Bhosale, S., Dettmers, T., Goyal, N., & Zettlemoyer, L. (2021) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 88

Efficient Streaming Language Models with Attention Sinks

Xiao, G., Tian, Y., Chen, B., Han, S., & Lewis, M. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 55

Shortformer: Better Language Modeling using Shorter Inputs

Press, O., Smith, N. A., & Lewis, M. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 55

Shortformer: Better language modeling using shorter inputs

Press, O., Smith, N. A., & Lewis, M. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 55

HTLM: Hyper-Text Pre-Training and Prompting of Language Models

Aghajanyan, A., Okhonko, D., Lewis, M., Joshi, M., Xu, H., Ghosh, G., & Zettlemoyer, L. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 35

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Min, S., Krishna, K., Lyu, X., Lewis, M., Yih, W.-T., Koh, P. W., Iyyer, M., Zettlemoyer, L., & Hajishirzi, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 14

Effective Long-Context Scaling of Foundation Models

Xiong, W., Liu, J., Molybog, I., Zhang, H., Bhargava, P., Hou, R., Martin, L., Rungta, R., Sankararaman, K. A., Oguz, B., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9