Xiangkun Hu
Orcid: 0009-0006-2165-9236
According to our database1,
Xiangkun Hu
authored at least 18 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
CoRR, 2024
RefChecker: Reference-based Fine-grained Hallucination Checker and Benchmark for Large Language Models.
CoRR, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Artificial intelligence based trust management for vehicular networks using blockchain.
Proceedings of the 8th International Conference on Information Systems Engineering, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
2022
BART-Reader: Predicting Relations Between Entities via Reading Their Document-Level Context Information.
Proceedings of the Natural Language Processing and Chinese Computing, 2022
RLET: A Reinforcement Learning Based Approach for Explainable QA with Entailment Trees.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
2021
IEEE Trans. Knowl. Data Eng., 2021
2019
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019
2018
Incorporating Argument-Level Interactions for Persuasion Comments Evaluation using Co-attention Model.
Proceedings of the 27th International Conference on Computational Linguistics, 2018