| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 2772 | 2021 |
| Wilds: A benchmark of in-the-wild distribution shifts PW Koh, S Sagawa, H Marklund, SM Xie, M Zhang, A Balsubramani, ... International conference on machine learning, 5637-5664, 2021 | 1168 | 2021 |
| Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task T Yu, R Zhang, K Yang, M Yasunaga, D Wang, Z Li, J Ma, I Li, Q Yao, ... Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 870 | 2018 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... Transactions on Machine Learning Research, 2022 | 755 | 2022 |
| Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022 | 662* | 2022 |
| Is ChatGPT a General-Purpose Natural Language Processing Task Solver? C Qin, A Zhang, Z Zhang, J Chen, M Yasunaga, D Yang arXiv preprint arXiv:2302.06476, 2023 | 449 | 2023 |
| QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering M Yasunaga, H Ren, A Bosselut, P Liang, J Leskovec Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 435 | 2021 |
| Graph-based Neural Multi-Document Summarization M Yasunaga, R Zhang, K Meelu, A Pareek, K Srinivasan, D Radev Proceedings of the 21st Conference on Computational Natural Language …, 2017 | 306 | 2017 |
| Unifiedskg: Unifying and multi-tasking structured knowledge grounding with text-to-text language models T Xie, CH Wu, P Shi, R Zhong, T Scholak, M Yasunaga, CS Wu, M Zhong, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 229* | 2022 |
| LinkBERT: Pretraining Language Models with Document Links M Yasunaga, J Leskovec, P Liang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 223 | 2022 |
| Replug: Retrieval-augmented black-box language models W Shi, S Min, M Yasunaga, M Seo, R James, M Lewis, L Zettlemoyer, ... arXiv preprint arXiv:2301.12652, 2023 | 216* | 2023 |
| SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task T Yu, M Yasunaga, K Yang, R Zhang, D Wang, Z Li, D Radev Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 209 | 2018 |
| ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks M Yasunaga, J Kasai, R Zhang, AR Fabbri, I Li, D Friedman, DR Radev Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 7386 …, 2019 | 203 | 2019 |
| GreaseLM: Graph REASoning Enhanced Language Models for Question Answering X Zhang, A Bosselut, M Yasunaga, H Ren, P Liang, CD Manning, ... International Conference on Learning Representations, 2022 | 177 | 2022 |
| Graph-based, Self-Supervised Program Repair from Diagnostic Feedback M Yasunaga, P Liang Proceedings of the 37th International Conference on Machine Learning, 2020 | 177 | 2020 |
| SParC: Cross-Domain Semantic Parsing in Context T Yu, R Zhang, M Yasunaga, YC Tan, XV Lin, S Li, H Er, I Li, B Pang, ... Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 174* | 2019 |
| Robust Multilingual Part-of-Speech Tagging via Adversarial Training M Yasunaga, J Kasai, D Radev Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 163 | 2018 |
| Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL) MK Chandrasekaran, P Mayr, M Yasunaga, D Freitag, D Radev, MY Kan Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 146* | 2019 |
| Deep Bidirectional Language-Knowledge Graph Pretraining M Yasunaga, A Bosselut, H Ren, X Zhang, CD Manning, P Liang, ... Advances in Neural Information Processing Systems, 2022 | 132 | 2022 |
| Break-It-Fix-It: Unsupervised Learning for Program Repair M Yasunaga, P Liang Proceedings of the 38th International Conference on Machine Learning, 2021 | 96 | 2021 |
Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
