The unreliability of explanations in few-shot prompting for textual reasoning X Ye, G Durrett Advances in neural information processing systems 35, 30378-30392, 2022 | 174* | 2022 |
RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering X Ye, S Yavuz, K Hashimoto, Y Zhou, C Xiong ACL 2022, 2021 | 125 | 2021 |
Multi-modal synthesis of regular expressions Q Chen, X Wang, X Ye, G Durrett, I Dillig Proceedings of the 41st ACM SIGPLAN Conference on Programming Language …, 2020 | 97 | 2020 |
Interactive correction of mislabeled training data S Xiang, X Ye, J Xia, J Wu, Y Chen, S Liu 2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 57-68, 2019 | 81 | 2019 |
Complementary Explanations for Effective In-Context Learning X Ye, S Iyer, A Celikyilmaz, V Stoyanov, G Durrett, R Pasunuru Findings of ACL 2023, 2022 | 73 | 2022 |
SatLM: Satisfiability-Aided Language Models Using Declarative Prompting X Ye, Q Chen, I Dillig, G Durrett Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 41 | 2023 |
Sketch-Driven Regular Expression Generation from Natural Language and Examples X Ye, Q Chen, X Wang, I Dillig, G Durrett Transactions of the Association for Computational Linguistics 8, 679-694, 2020 | 39 | 2020 |
Connecting Attributions and QA Model Behavior on Realistic Counterfactuals X Ye, R Nair, G Durrett Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 27* | 2021 |
Optimal Neural Program Synthesis from Multimodal Specifications X Ye, Q Chen, I Dillig, G Durrett Findings of EMNLP 2021, 2020 | 27 | 2020 |
Diagnosing ensemble few-shot classifiers W Yang, X Ye, X Zhang, L Xiao, J Xia, Z Wang, J Zhu, H Pfister, S Liu IEEE Transactions on Visualization and Computer Graphics 28 (9), 3292-3306, 2022 | 25 | 2022 |
Can Explanations Be Useful for Calibrating Black Box Models? X Ye, G Durrett ACL 2022, 2021 | 24 | 2021 |
Benchmarking Multimodal Regex Synthesis with Complex Structures X Ye, Q Chen, I Dillig, G Durrett ACL 2020, 2020 | 23 | 2020 |
MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning Z Sprague, X Ye, K Bostrom, S Chaudhuri, G Durrett arXiv preprint arXiv:2310.16049, 2023 | 22* | 2023 |
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning Z Sprague, F Yin, JD Rodriguez, D Jiang, M Wadhwa, P Singhal, X Zhao, ... arXiv preprint arXiv:2409.12183, 2024 | 18 | 2024 |
Effective large language model adaptation for improved grounding and citation generation X Ye, R Sun, SÖ Arik, T Pfister NAACL 2024, 2023 | 18* | 2023 |
Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting X Ye, G Durrett EMNLP 2023, 2023 | 17* | 2023 |
Crafting In-context Examples according to LMs' Parametric Knowledge Y Lee, P Atreya, X Ye, E Choi arXiv preprint arXiv:2311.09579, 2023 | 8 | 2023 |
Explanation in the Era of Large Language Models Z Zhu, H Chen, X Ye, Q Lyu, C Tan, A Marasović, S Wiegreffe Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | 5 | 2024 |
Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning X Zhang, ZZ Chen, X Ye, X Yang, L Chen, WY Wang, LR Petzold arXiv preprint arXiv:2405.20535, 2024 | 5 | 2024 |
Assessing Out-of-Domain Language Model Performance from Few Examples P Singhal, J Forristal, X Ye, G Durrett arXiv preprint arXiv:2210.06725, 2022 | 5 | 2022 |