| Self-Instruct: Aligning Language Models with Self-Generated Instructions Y Wang, Y Kordi, S Mishra, A Liu, NA Smith, D Khashabi, H Hajishirzi ACL, 2023 | 1125 | 2023 |
| DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs D Dua, Y Wang, P Dasigi, G Stanovsky, S Singh, M Gardner NAACL, 2019 | 783 | 2019 |
| Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks Y Wang*, S Mishra*, P Alipoormolabashi, Y Kordi, A Mirzaei, A Arunkumar, ... EMNLP, 2022 | 447* | 2022 |
| Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics S Swayamdipta, R Schwartz, N Lourie, Y Wang, H Hajishirzi, NA Smith, ... EMNLP, 2020 | 330 | 2020 |
| Dureader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications W He, K Liu, J Liu, Y Lyu, S Zhao, X Xiao, Y Liu, Y Wang, H Wu, Q She, ... Workshop on Machine Reading for Question Answering (MRQA), 2018 | 300 | 2018 |
| Do NLP Models Know Numbers? Probing Numeracy in Embeddings E Wallace*, Y Wang*, S Li, S Singh, M Gardner EMNLP, 2019 | 275 | 2019 |
| How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources Y Wang*, H Ivison*, P Dasigi, J Hessel, T Khot, KR Chandu, D Wadden, ... NeurIPS, 2023 | 168 | 2023 |
| One Embedder, Any Task: Instruction-Finetuned Text Embeddings H Su, W Shi, J Kasai, Y Wang, Y Hu, M Ostendorf, W Yih, NA Smith, ... ACL, 2023 | 139 | 2023 |
| Multi-Passage Machine Reading Comprehension with Cross-passage Answer Verification Y Wang, K Liu, J Liu, W He, Y Lyu, H Wu, S Li, H Wang ACL, 2018 | 126 | 2018 |
| Self-RAG: Learning to retrieve, generate, and critique through self-reflection A Asai, Z Wu, Y Wang, A Sil, H Hajishirzi ICLR, 2023 | 121 | 2023 |
| A Two-Stage Parsing Method for Text-Level Discourse Analysis Y Wang, S Li, H Wang ACL, 2017 | 120 | 2017 |
| MultiModalQA: Complex Question Answering over Text, Tables and Images A Talmor, O Yoran, A Catav, D Lahav, Y Wang, A Asai, G Ilharco, ... ICLR, 2021 | 115 | 2021 |
| Toward Fast and Accurate Neural Discourse Segmentation Y Wang, S Li, J Yang EMNLP, 2018 | 96 | 2018 |
| Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering Y Hu, B Liu, J Kasai, Y Wang, M Ostendorf, R Krishna, NA Smith ICCV, 2023 | 81 | 2023 |
| Bag-of-Words as Target for Neural Machine Translation S Ma, X Sun, Y Wang, J Lin ACL, 2018 | 73 | 2018 |
| Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 H Ivison*, Y Wang*, V Pyatkin, N Lambert, M Peters, P Dasigi, J Jang, ... arXiv preprint arXiv:2311.10702, 2023 | 72 | 2023 |
| Probing Across Time: What Does RoBERTa Know and When? LZ Liu*, Y Wang*, J Kasai, H Hajishirzi, NA Smith EMNLP Findings, 2021 | 66 | 2021 |
| Automated Lay Language Summarization of Biomedical Scientific Reviews Y Guo, W Qiu, Y Wang, T Cohen AAAI, 2021 | 61 | 2021 |
| Personalized soups: Personalized large language model alignment via post-hoc parameter merging J Jang, S Kim, BY Lin, Y Wang, J Hessel, L Zettlemoyer, H Hajishirzi, ... arXiv preprint arXiv:2310.11564, 2023 | 42 | 2023 |
| The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus A Piktus, F Petroni, Y Wang, V Karpukhin, D Okhonko, S Broscheit, ... arXiv preprint arXiv:2112.09924, 2021 | 41 | 2021 |
Hannaneh HajishirziUniversity of Washington; Allen AI在 cs.washington.edu 的电子邮件经过验证
