Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses

Hung-Ting Su, Ya-Ching Hsu, Xudong Lin, Xiang-Qian Shi, Yulei Niu, Han-Yuan Hsu, Hung-yi Lee, Winston H. Hsu


Abstract
Large language models (LLMs) equipped with chain-of-thoughts (CoT) prompting have shown significant multi-step reasoning capabilities in factual content like mathematics, commonsense, and logic. However, their performance in narrative reasoning, which demands greater abstraction capabilities, remains unexplored. This study utilizes tropes in movie synopses to assess the abstract reasoning abilities of state-of-the-art LLMs and uncovers their low performance. We introduce a trope-wise querying approach to address these challenges and boost the F1 score by 11.8 points. Moreover, while prior studies suggest that CoT enhances multi-step reasoning, this study shows CoT can cause hallucinations in narrative content, reducing GPT-4’s performance. We also introduce an Adversarial Injection method to embed trope-related text tokens into movie synopses without explicit tropes, revealing CoT’s heightened sensitivity to such injections. Our comprehensive analysis provides insights for future research directions.
Anthology ID:
2024.findings-emnlp.872
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2024
Month:
November
Year:
2024
Address:
Miami, Florida, USA
Editors:
Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
14839–14854
Language:
URL:
https://aclanthology.org/2024.findings-emnlp.872/
DOI:
10.18653/v1/2024.findings-emnlp.872
Bibkey:
Cite (ACL):
Hung-Ting Su, Ya-Ching Hsu, Xudong Lin, Xiang-Qian Shi, Yulei Niu, Han-Yuan Hsu, Hung-yi Lee, and Winston H. Hsu. 2024. Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 14839–14854, Miami, Florida, USA. Association for Computational Linguistics.
Cite (Informal):
Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses (Su et al., Findings 2024)
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PDF:
https://aclanthology.org/2024.findings-emnlp.872.pdf