| Toolformer: Language models can teach themselves to use tools T Schick, J Dwivedi-Yu, R Dessì, R Raileanu, M Lomeli, L Zettlemoyer, ... Neural Information Processing Systems (NeurIPS), 2023 | 1066 | 2023 |
| Atlas: Few-shot learning with retrieval augmented language models G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni, T Schick, ... Journal of Machine Learning Research (JMLR), 2023 | 498* | 2023 |
| Augmented language models: a survey G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ... Transactions on Machine Learning Research (TMLR), 2023 | 393 | 2023 |
| Active retrieval augmented generation Z Jiang, FF Xu, L Gao, Z Sun, Q Liu, J Dwivedi-Yu, Y Yang, J Callan, ... Empirical Methods in Natural Language Processing (EMNLP), 2023 | 210 | 2023 |
| PEER: A Collaborative Language Model T Schick, J Dwivedi-Yu, Z Jiang, F Petroni, P Lewis, G Izacard, Q You, ... International Conference on Learning Representations (ICLR), 2023 | 96* | 2023 |
| The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems C Ziems, JA Yu, YC Wang, A Halevy, D Yang Association for Computational Linguistics (ACL), 2022 | 81 | 2022 |
| Shepherd: A critic for language model generation T Wang, P Yu, XE Tan, S O'Brien, R Pasunuru, J Dwivedi-Yu, ... arXiv preprint arXiv:2308.04592, 2023 | 39 | 2023 |
| Active Learning Principles for In-Context Learning with Large Language Models K Margatina, T Schick, N Aletras, J Dwivedi-Yu Empirical Methods in Natural Language Processing (EMNLP) [Findings], 2023 | 31 | 2023 |
| Worldwide genetic variation of the IGHV and TRBV immune receptor gene families in humans S Luo, AY Jane, H Li, YS Song Life Science Alliance, 2019 | 31 | 2019 |
| Estimating copy number and allelic variation at the immunoglobulin heavy chain locus using short reads S Luo, JA Yu, YS Song PLoS Computational Biology, 2016 | 31 | 2016 |
| NormBank: A Knowledge Bank of Situational Social Norms C Ziems, J Dwivedi-Yu, YC Wang, A Halevy, D Yang Association for Computational Linguistics (ACL), 2023 | 26 | 2023 |
| ROBBIE: Robust bias evaluation of large generative language models D Esiobu, X Tan, S Hosseini, M Ung, Y Zhang, J Fernandes, J Dwivedi-Yu, ... Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 21 | 2023 |
| Editeval: An instruction-based benchmark for text improvements J Dwivedi-Yu, T Schick, Z Jiang, M Lomeli, P Lewis, G Izacard, E Grave, ... arXiv preprint arXiv:2209.13331, 2022 | 18 | 2022 |
| Improving wikipedia verifiability with ai F Petroni, S Broscheit, A Piktus, P Lewis, G Izacard, L Hosseini, ... Nature Machine Intelligence 5 (10), 1142-1148, 2023 | 17 | 2023 |
| Quantifying Adaptability in Pre-trained Language Models with 500 Tasks BZ Li, J Yu, M Khabsa, L Zettlemoyer, A Halevy, J Andreas North American Chapter of the Association for Computational Linguistics (NAACL), 2021 | 15 | 2021 |
| Teaching large language models to reason with reinforcement learning A Havrilla, Y Du, SC Raparthy, C Nalmpantis, J Dwivedi-Yu, ... arXiv preprint arXiv:2403.04642, 2024 | 12 | 2024 |
| Understanding conflicts in online conversations S Levy, RE Kraut, JA Yu, KM Altenburger, YC Wang International World Wide Web Conference (WWW), 2592-2602, 2022 | 12 | 2022 |
| Learnings from data integration for augmented language models A Halevy, J Dwivedi-Yu arXiv preprint arXiv:2304.04576, 2023 | 11 | 2023 |
| Efficient Tool Use with Chain-of-Abstraction Reasoning S Gao, J Dwivedi-Yu, P Yu, XE Tan, R Pasunuru, O Golovneva, K Sinha, ... arXiv preprint arXiv:2401.17464, 2024 | 8 | 2024 |
| Glore: When, where, and how to improve llm reasoning via global and local refinements A Havrilla, S Raparthy, C Nalmpantis, J Dwivedi-Yu, M Zhuravinskyi, ... arXiv preprint arXiv:2402.10963, 2024 | 7 | 2024 |
Timo SchickNLP ResearcherVerified email at fb.com