| 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 | 196* | 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 | 144 | 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 | 102 | 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 | 86 | 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 | 80 | 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 | 56 | 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 |
| 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 | 35* | 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 | 34 | 2024 |
| Optimal Neural Program Synthesis from Multimodal Specifications X Ye, Q Chen, I Dillig, G Durrett Findings of EMNLP 2021, 2020 | 29 | 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 | 28 | 2022 |
| 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 |
| Can Explanations Be Useful for Calibrating Black Box Models? X Ye, G Durrett ACL 2022, 2021 | 25 | 2021 |
| Effective large language model adaptation for improved grounding and citation generation X Ye, R Sun, SÖ Arik, T Pfister NAACL 2024, 2023 | 23* | 2023 |
| Benchmarking Multimodal Regex Synthesis with Complex Structures X Ye, Q Chen, I Dillig, G Durrett ACL 2020, 2020 | 23 | 2020 |
| Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting X Ye, G Durrett EMNLP 2023, 2023 | 18* | 2023 |
| LoFiT: Localized Fine-tuning on LLM Representations F Yin, X Ye, G Durrett arXiv preprint arXiv:2406.01563, 2024 | 9 | 2024 |
| 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 | 7 | 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 | 6 | 2024 |