Benchmarking Temporal Reasoning and Alignment Across Chinese Dynasties
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910842485735424 |
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| author | Wang, Zhenglin Wu, Jialong LI, Pengfei Jiang, Yong Zhou, Deyu |
| author_facet | Wang, Zhenglin Wu, Jialong LI, Pengfei Jiang, Yong Zhou, Deyu |
| contents | Temporal reasoning is fundamental to human cognition and is crucial for various real-world applications. While recent advances in Large Language Models have demonstrated promising capabilities in temporal reasoning, existing benchmarks primarily rely on rule-based construction, lack contextual depth, and involve a limited range of temporal entities. To address these limitations, we introduce Chinese Time Reasoning (CTM), a benchmark designed to evaluate LLMs on temporal reasoning within the extensive scope of Chinese dynastic chronology. CTM emphasizes cross-entity relationships, pairwise temporal alignment, and contextualized and culturally-grounded reasoning, providing a comprehensive evaluation. Extensive experimental results reveal the challenges posed by CTM and highlight potential avenues for improvement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_16922 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Benchmarking Temporal Reasoning and Alignment Across Chinese Dynasties Wang, Zhenglin Wu, Jialong LI, Pengfei Jiang, Yong Zhou, Deyu Computation and Language Temporal reasoning is fundamental to human cognition and is crucial for various real-world applications. While recent advances in Large Language Models have demonstrated promising capabilities in temporal reasoning, existing benchmarks primarily rely on rule-based construction, lack contextual depth, and involve a limited range of temporal entities. To address these limitations, we introduce Chinese Time Reasoning (CTM), a benchmark designed to evaluate LLMs on temporal reasoning within the extensive scope of Chinese dynastic chronology. CTM emphasizes cross-entity relationships, pairwise temporal alignment, and contextualized and culturally-grounded reasoning, providing a comprehensive evaluation. Extensive experimental results reveal the challenges posed by CTM and highlight potential avenues for improvement. |
| title | Benchmarking Temporal Reasoning and Alignment Across Chinese Dynasties |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2502.16922 |