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AttuneBench: A Conversation-Based Benchmark for LLM Emotional Intelligence

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arXiv:2605. 21739v1 Announce Type: new Abstract: Emotional intelligence (EI), the ability to perceive, understand, and respond appropriately to others' emotional states, is central to human communication, and increasingly important to assess as LLMs assume conversational roles in everyday life.

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Authors: Kate M. Lubrano, Faisal Sayed, Ankita Rathod, Akshansh, Craver Corbyn Thomas-Smith, Mark E. Whiting, Karina Nguyen
Released: 2026-05-23 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because AttuneBench: A Conversation-Based Benchmark for LLM Emotional Intelligence overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, class, rect, under, alignment, eval, model. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2605.21739

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