| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1208 | 2023 |
| Crosslingual generalization through multitask finetuning N Muennighoff, T Wang, L Sutawika, A Roberts, S Biderman, TL Scao, ... ACL 2023, 2022 | 373 | 2022 |
| PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts SH Bach, V Sanh, ZX Yong, A Webson, C Raffel, NV Nayak, A Sharma, ... ACL 2022, 2022 | 243 | 2022 |
| RWKV: Reinventing RNNs for the Transformer Era B Peng, E Alcaide, Q Anthony, A Albalak, S Arcadinho, H Cao, X Cheng, ... EMNLP 2023, 2023 | 187* | 2023 |
| Toolllm: Facilitating large language models to master 16000+ real-world apis Y Qin, S Liang, Y Ye, K Zhu, L Yan, Y Lu, Y Lin, X Cong, X Tang, B Qian, ... ICLR 2024, 2023 | 178 | 2023 |
| Dart: Open-domain structured data record to text generation L Nan, D Radev, R Zhang, A Rau, A Sivaprasad, C Hsieh, X Tang, A Vyas, ... TACL 2021, 2021 | 164* | 2021 |
| FeTaQA: Free-form Table Question Answering L Nan, C Hsieh, Z Mao, XV Lin, N Verma, R Zhang, W Kryściński, ... TACL 2022, 2022 | 66* | 2022 |
| Survey on factuality in large language models: Knowledge, retrieval and domain-specificity C Wang, X Liu, Y Yue, X Tang, T Zhang, C Jiayang, Y Yao, W Gao, X Hu, ... arXiv preprint arXiv:2310.07521, 2023 | 59 | 2023 |
| Octopack: Instruction tuning code large language models N Muennighoff, Q Liu, A Zebaze, Q Zheng, B Hui, TY Zhuo, S Singh, ... ICLR 2024, 2023 | 55 | 2023 |
| CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning X Tang, A Nair, B Wang, B Wang, J Desai, A Wade, H Li, A Celikyilmaz, ... NAACL 2022, 2021 | 51 | 2021 |
| Agents: An open-source framework for autonomous language agents W Zhou, YE Jiang, L Li, J Wu, T Wang, S Qiu, J Zhang, J Chen, R Wu, ... arXiv preprint arXiv:2309.07870, 2023 | 33 | 2023 |
| Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types S Mo, X Fu, C Hong, Y Chen, Y Zheng, X Tang, Z Shen, EP Xing, Y Lan NeurIPS 2021 AI for Science, 2021 | 20* | 2021 |
| Investigating data contamination in modern benchmarks for large language models C Deng, Y Zhao, X Tang, M Gerstein, A Cohan NAAACL 2024, 2023 | 18* | 2023 |
| Categorizing Offensive Language in Social Networks: A Chinese Corpus, Systems and an Explanation Tool X Tang, X Shen, Y Wang, Y Yang CCL 2020, 2020 | 16 | 2020 |
| Investigating Crowdsourcing Protocols for Evaluatingthe Factual Consistency of Summaries X Tang, AR Fabbri, Z Mao, G Adams, B Wang, H Li, Y Mehdad, D Radev NAACL 2022, 2021 | 14 | 2021 |
| Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents Z Zhang, Y Yao, A Zhang, X Tang, X Ma, Z He, Y Wang, M Gerstein, ... arXiv preprint arXiv:2311.11797, 2023 | 13 | 2023 |
| Medagents: Large language models as collaborators for zero-shot medical reasoning X Tang, A Zou, Z Zhang, Y Zhao, X Zhang, A Cohan, M Gerstein arXiv preprint arXiv:2311.10537, 2023 | 13 | 2023 |
| StarCoder 2 and The Stack v2: The Next Generation A Lozhkov, R Li, LB Allal, F Cassano, J Lamy-Poirier, N Tazi, A Tang, ... arXiv preprint arXiv:2402.19173, 2024 | 9 | 2024 |
| Robut: A systematic study of table qa robustness against human-annotated adversarial perturbations Y Zhao, C Zhao, L Nan, Z Qi, W Zhang, X Tang, B Mi, D Radev arXiv preprint arXiv:2306.14321, 2023 | 9 | 2023 |
| Struc-Bench: Are Large Language Models Good at Generating Complex Structured Tabular Data? X Tang, Y Zong, J Phang, Y Zhao, W Zhou, A Cohan, M Gerstein NAACL 2024, 2023 | 8* | 2023 |
Mark GersteinProfessor of Biomedical Informatics, Yale UniversityVerified email at yale.edu
