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Academically intelligent LLMs are not necessarily socially intelligent

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arxiv 2403.06591 v1 pith:IGTIGCHT submitted 2024-03-11 cs.CL cs.CY

classification cs.CLcs.CY
keywords intelligencesocialllmsacademicevaluationintelligentrecentsesi
verification ladder T0 review T1 audit T2 compute T3 formal
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The academic intelligence of large language models (LLMs) has made remarkable progress in recent times, but their social intelligence performance remains unclear. Inspired by established human social intelligence frameworks, particularly Daniel Goleman's social intelligence theory, we have developed a standardized social intelligence test based on real-world social scenarios to comprehensively assess the social intelligence of LLMs, termed as the Situational Evaluation of Social Intelligence (SESI). We conducted an extensive evaluation with 13 recent popular and state-of-art LLM agents on SESI. The results indicate the social intelligence of LLMs still has significant room for improvement, with superficially friendliness as a primary reason for errors. Moreover, there exists a relatively low correlation between the social intelligence and academic intelligence exhibited by LLMs, suggesting that social intelligence is distinct from academic intelligence for LLMs. Additionally, while it is observed that LLMs can't ``understand'' what social intelligence is, their social intelligence, similar to that of humans, is influenced by social factors.

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  1. LIFELONG SOTOPIA: Evaluating Social Intelligence of Language Agents Over Lifelong Social Interactions

    cs.AI 2025-06 conditional novelty 6.0 of 10

    Language agents' believability and goal achievement decline over multi-episode social interactions, and curated memory summaries only partially close the gap with humans.

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