| Towards explainable NLP: A generative explanation framework for text classification H Liu, Q Yin, WY Wang Proceedings of the 57th Conference of the Association for Computational …, 2019 | 225 | 2019 |
| End-to-End Transition-Based Online Dialogue Disentanglement H Liu, Z Shi, JC Gu, Q Liu, S Wei, X Zhu IJCAI, 3868--3874, 2020 | 28 | 2020 |
| Unsupervised Conversation Disentanglement through Co-Training H Liu, Z Shi, X Zhu EMNLP 2021, 2021 | 26 | 2021 |
| Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbots JC Gu, H Liu, ZH Ling, Q Liu, Z Chen, X Zhu SIGIR 2021, 2021 | 25 | 2021 |
| Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning H Liu, D Zhang, B Yin, X Zhu NAACL-HLT 2021, 2021 | 22 | 2021 |
| Enhancing Descriptive Image Captioning with Natural Language Inference Z Shi, H Liu, X Zhu ACL-IJCNLP 2021, 2021 | 22 | 2021 |
| QuoteRec: Toward quote recommendation for writing J Tan, X Wan, H Liu, J Xiao ACM Transactions on Information Systems (TOIS) 36 (3), 1-36, 2018 | 21 | 2018 |
| Interpretable Low-Resource Legal Decision Making R Bhambhoria, H Liu, S Dahan, X Zhu AAAI 2022, 2022 | 10 | 2022 |
| Retrieval, analogy, and composition: A framework for compositional generalization in image captioning Z Shi, H Liu, MR Min, C Malon, LE Li, X Zhu Findings of the Association for Computational Linguistics: EMNLP 2021, 1990-2000, 2021 | 6 | 2021 |
| Simrag: Self-improving retrieval-augmented generation for adapting large language models to specialized domains R Xu, H Liu, S Nag, Z Dai, Y Xie, X Tang, C Luo, Y Li, JC Ho, C Yang, ... arXiv preprint arXiv:2410.17952, 2024 | 2 | 2024 |
| Descriptive Image Captioning with Salient Retrieval Priors Z Shi, H Liu, X Zhu Canadian Conference on Artificial Intelligence 2021, 2021 | 2 | 2021 |
| Towards knowledge checking in retrieval-augmented generation: A representation perspective S Zeng, J Zhang, B Li, Y Lin, T Zheng, D Everaert, H Lu, H Liu, Y Xing, ... arXiv preprint arXiv:2411.14572, 2024 | 1 | 2024 |
| Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge Z Zhang, F Wang, X Li, Z Wu, X Tang, H Liu, Q He, W Yin, S Wang arXiv e-prints, arXiv: 2410.16454, 2024 | 1 | 2024 |
| Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning H Han, Y Xie, H Liu, X Tang, S Nag, W Headden, Y Li, C Luo, S Ji, Q He, ... arXiv preprint arXiv:2501.07845, 2025 | | 2025 |
| A Survey of Calibration Process for Black-Box LLMs L Xie, H Liu, J Zeng, X Tang, Y Han, C Luo, J Huang, Z Li, S Wang, Q He arXiv preprint arXiv:2412.12767, 2024 | | 2024 |
| Exploring Query Understanding for Amazon Product Search C Luo, X Tang, H Lu, Y Xie, H Liu, Z Dai, L Cui, A Joshi, S Nag, Y Li, Z Li, ... 2024 IEEE International Conference on Big Data (BigData), 2343-2348, 2024 | | 2024 |
| Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data J Li, S Nag, H Liu, X Tang, S Sarwar, L Cui, H Gu, S Wang, Q He, J Tang arXiv preprint arXiv:2411.08028, 2024 | | 2024 |
| Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions X Zhang, X Tang, H Liu, Z Wu, Q He, D Lee, S Wang arXiv preprint arXiv:2410.12207, 2024 | | 2024 |
| Knowledge-Selective Pretraining for Attribute Value Extraction H Liu, Q Yin, Z Wang, C Zhang, H Jiang, Y Gao, Z Li, X Li, C Zhang, B Yin, ... Findings of EMNLP 2023, 2023 | | 2023 |
| Deep Learning Models for Topic Classification and Disentanglement H Liu | | 2023 |
Xiaodan ZhuECE & Ingenuity Labs Research Institute, Queen's University, CanadaVerified email at queensu.ca
