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Fusion Makes Perfection: An Efficient Multi-Grained Matching Approach for Zero-Shot Relation Extraction
Published in Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), Main Conference, 2024
An efficient multi-grained matching approach for zero-shot relation extraction.
Recommended citation: Shilong Li*, Ge Bai*, Zhang Zhang*, et al. "Fusion Makes Perfection: An Efficient Multi-Grained Matching Approach for Zero-Shot Relation Extraction." NAACL 2024.
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GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models
Published in Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2024
A graph-based agent approach to enhance long-context abilities of LLMs.
Recommended citation: Shilong Li*, Yancheng He*, Hangyu Guo*, Xingyuan Bu*, et al. "GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models." EMNLP Findings 2024.
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2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision
Published in Findings of the North American Chapter of the Association for Computational Linguistics (NAACL Findings), 2025
Scaling direct preference optimization with 2-dimensional supervision signals.
Recommended citation: Shilong Li*, Yancheng He*, Hui Huang, et al. "2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision." NAACL Findings 2025.
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Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models
Published in Proceedings of the Association for Computational Linguistics (ACL), Main Conference, 2025
A Chinese factuality evaluation benchmark for large language models.
Recommended citation: Yancheng He*, Shilong Li*, Jiaheng Liu*, et al. "Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models." ACL 2025.
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Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?
Published in Proceedings of the Association for Computational Linguistics (ACL), Main Conference, 2025
A study on evaluating LLMs ability to detect errors in long chain-of-thought reasoning.
Recommended citation: Yancheng He*, Shilong Li*, Jiaheng Liu*, et al. "Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?" ACL 2025.
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MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Published in arXiv preprint arXiv:2508.13186, 2025
A comprehensive benchmark for evaluating multimodal browsing agents.
Recommended citation: Shilong Li*, Xingyuan Bu*, Wenjie Wang, Jiaheng Liu, et al. "MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents." arXiv 2025.
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