TimeHC-RL: Temporal-aware Hierarchical Cognitive Reinforcement Learning for Enhancing LLMs' Social Intelligence Article Swipe

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Guiyang Hou , Xing Gao , Yuchuan Wu , Xiang Huang , Wenqi Zhang , Zhe Zheng , Yongliang Shen , Jialu Du , Fei Huang , Yongbin Li , Weiming Lü ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2505.24500

Recently, Large Language Models (LLMs) have made significant progress in IQ-related domains that require careful thinking, such as mathematics and coding. However, enhancing LLMs' cognitive development in social domains, particularly from a post-training perspective, remains underexplored. Recognizing that the social world follows a distinct timeline and requires a richer blend of cognitive modes (from intuitive reactions (System 1) and surface-level thinking to deliberate thinking (System 2)) than mathematics, which primarily relies on System 2 cognition (careful, step-by-step reasoning), we introduce Temporal-aware Hierarchical Cognitive Reinforcement Learning (TimeHC-RL) for enhancing LLMs' social intelligence. In our experiments, we systematically explore improving LLMs' social intelligence and validate the effectiveness of the TimeHC-RL method, through five other post-training paradigms and two test-time intervention paradigms on eight datasets with diverse data patterns. Experimental results reveal the superiority of our proposed TimeHC-RL method compared to the widely adopted System 2 RL method. It gives the 7B backbone model wings, enabling it to rival the performance of advanced models like DeepSeek-R1 and OpenAI-O3. Additionally, the systematic exploration from post-training and test-time interventions perspectives to improve LLMs' social intelligence has uncovered several valuable insights.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2505.24500
PDF: https://arxiv.org/pdf/2505.24500
OA Status: green
OpenAlex ID: https://openalex.org/W4414857714

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DOI: https://doi.org/10.48550/arxiv.2505.24500

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Title: TimeHC-RL: Temporal-aware Hierarchical Cognitive Reinforcement Learning for Enhancing LLMs' Social Intelligence

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-05-30

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Authors: Guiyang Hou, Xing Gao, Yuchuan Wu, Xiang Huang, Wenqi Zhang, Zhe Zheng, Yongliang Shen, Jialu Du, Fei Huang, Yongbin Li, Weiming Lü

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Landing page: https://arxiv.org/abs/2505.24500

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PDF URL: https://arxiv.org/pdf/2505.24500

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Cited by: 0

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