Lewis, Patrick

Dense Passage Retrieval for Open-Domain Question Answering

Karpukhin, V., Oğuz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W.-T. (2020) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 5,311

Dense passage retrieval for open-domain question answering

Karpukhin, V., Oguz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W.-T. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 3,575

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

Language Models as Knowledge Bases?

Petroni, F., Rocktäschel, T., Riedel, S., Lewis, P., Bakhtin, A., Wu, Y., & Miller, A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 1,834

KILT: a Benchmark for Knowledge Intensive Language Tasks

Petroni, F., Piktus, A., Fan, A., Lewis, P., Yazdani, M., De Cao, N., Thorne, J., Jernite, Y., Karpukhin, V., Maillard, J., et al. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 357

Atlas: Few-shot Learning with Retrieval Augmented Language Models

Izacard, G., Lewis, P., Lomeli, M., Hosseini, L., Petroni, F., Schick, T., Dwivedi-Yu, J., Joulin, A., Riedel, S., & Grave, E. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 213

How Context Affects Language Models' Factual Predictions

Petroni, F., Lewis, P., Piktus, A., Rocktäschel, T., Wu, Y., Miller, A. H., & Riedel, S. (2020) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 154

Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets

Lewis, P., Stenetorp, P., & Riedel, S. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Topic ModelingInformation Retrieval and Search Behavior

Cited by 145

Interpretation of Natural Language Rules in Conversational Machine Reading

Saeidi, M., Bartolo, M., Lewis, P., Singh, S., Rocktäschel, T., Sheldon, M., Bouchard, G., & Riedel, S. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 141

Unsupervised Question Decomposition for Question Answering

Perez, E., Lewis, P., Yih, W.-T., Cho, K., & Kiela, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 123

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Xiong, W., Li, X. L., Iyer, S., Du, J., Lewis, P., Wang, W. Y., Mehdad, Y., Yih, W.-T., Riedel, S., Kiela, D., et al. (2020) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 112

Autoregressive Search Engines: Generating Substrings as Document Identifiers

Bevilacqua, M., Ottaviano, G., Lewis, P., Yih, W.-T., Riedel, S., & Petroni, F. (2022) · arXiv

Algorithms and Data CompressionInformation Retrieval and Search Behavior

Cited by 80

SnapKV: LLM Knows What You are Looking for Before Generation

Li, Y., Huang, Y., Yang, B., Venkitesh, B., Locatelli, A., Ye, H., Cai, T., Lewis, P., & Chen, D. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 74

PEER: A Collaborative Language Model

Schick, T., Dwivedi-Yu, J., Jiang, Z., Petroni, F., Lewis, P., Izacard, G., You, Q., Nalmpantis, C., Grave, E., & Riedel, S. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

Task-aware Retrieval with Instructions

Asai, A., Schick, T., Lewis, P., Chen, X., Izacard, G., Riedel, S., Hajishirzi, H., & Yih, W.-T. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Information Retrieval and Search BehaviorTopic Modeling

Cited by 46

On the challenges of using black-box APIs for toxicity evaluation in research

Pozzobon, L., Ermis, B., Lewis, P., & Hooker, S. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 29

The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus

Piktus, A., Petroni, F., Karpukhin, V., Okhonko, D., Broscheit, S., Izacard, G., Lewis, P., Oğuz, B., Grave, E., Yih, W.-T., et al. (2021) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 22

Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models

Verga, P., Hofstatter, S., Althammer, S., Su, Y., Piktus, A., Arkhangorodsky, A., Xu, M., White, N., & Lewis, P. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16