| Auto-em: End-to-end fuzzy entity-matching using pre-trained deep models and transfer learning C Zhao, Y He The World Wide Web Conference, 2413-2424, 2019 | 157 | 2019 |
| Transformer-xh: Multi-evidence reasoning with extra hop attention C Zhao, C Xiong, C Rosset, X Song, P Bennett, S Tiwary International conference on learning representations, 2020 | 131 | 2020 |
| On the potential of lexico-logical alignments for semantic parsing to SQL queries T Shi, C Zhao, J Boyd-Graber, H Daumé III, L Lee arXiv preprint arXiv:2010.11246, 2020 | 71 | 2020 |
| On the relation between sensitivity and accuracy in in-context learning Y Chen, C Zhao, Z Yu, K McKeown, H He arXiv preprint arXiv:2209.07661, 2022 | 60 | 2022 |
| Dataset and baselines for sequential open-domain question answering A Elgohary, C Zhao, J Boyd-Graber Empirical methods in natural language processing, 2018 | 52 | 2018 |
| Do models explain themselves? counterfactual simulatability of natural language explanations Y Chen, R Zhong, N Ri, C Zhao, H He, J Steinhardt, Z Yu, K McKeown arXiv preprint arXiv:2307.08678, 2023 | 48 | 2023 |
| Complex factoid question answering with a free-text knowledge graph C Zhao, C Xiong, X Qian, J Boyd-Graber Proceedings of the web conference 2020, 1205-1216, 2020 | 46 | 2020 |
| Lightnet: A versatile, standalone matlab-based environment for deep learning C Ye, C Zhao, Y Yang, C Fermüller, Y Aloimonos Proceedings of the 24th ACM international conference on Multimedia, 1156-1159, 2016 | 32 | 2016 |
| Multi-step reasoning over unstructured text with beam dense retrieval C Zhao, C Xiong, J Boyd-Graber, H Daumé III arXiv preprint arXiv:2104.05883, 2021 | 30 | 2021 |
| Large Language Models Help Humans Verify Truthfulness--Except When They Are Convincingly Wrong C Si, N Goyal, ST Wu, C Zhao, S Feng, H Daumé III, J Boyd-Graber arXiv preprint arXiv:2310.12558, 2023 | 29 | 2023 |
| Two failures of self-consistency in the multi-step reasoning of LLMs A Chen, J Phang, A Parrish, V Padmakumar, C Zhao, SR Bowman, K Cho arXiv preprint arXiv:2305.14279, 2023 | 29 | 2023 |
| 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 | 27 | 2023 |
| Re-examining calibration: The case of question answering C Si, C Zhao, S Min, J Boyd-Graber arXiv preprint arXiv:2205.12507, 2022 | 25 | 2022 |
| What's in a name? answer equivalence for open-domain question answering C Si, C Zhao, J Boyd-Graber arXiv preprint arXiv:2109.05289, 2021 | 25 | 2021 |
| ARGUS: Visualization of AI-Assisted Task Guidance in AR S Castelo, J Rulff, E McGowan, B Steers, G Wu, S Chen, I Roman, ... IEEE Transactions on Visualization and Computer Graphics 30 (1), 1313-1323, 2023 | 21 | 2023 |
| Getting more out of mixture of language model reasoning experts C Si, W Shi, C Zhao, L Zettlemoyer, J Boyd-Graber arXiv preprint arXiv:2305.14628, 2023 | 19 | 2023 |
| Bridging the generalization gap in text-to-SQL parsing with schema expansion C Zhao, Y Su, A Pauls, EA Platanios Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 16 | 2022 |
| Parallel structures in pre-training data yield in-context learning Y Chen, C Zhao, Z Yu, K McKeown, H He arXiv preprint arXiv:2402.12530, 2024 | 12 | 2024 |
| Distantly-supervised dense retrieval enables open-domain question answering without evidence annotation C Zhao, C Xiong, J Boyd-Graber, HD Iii Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 12 | 2021 |
| Financemath: Knowledge-intensive math reasoning in finance domains Y Zhao, H Liu, Y Long, R Zhang, C Zhao, A Cohan arXiv preprint arXiv:2311.09797, 2023 | 11 | 2023 |
Jordan Boyd-GraberFull Professor, University of MarylandZweryfikowany adres z umiacs.umd.edu