mlsanityData to 14 Oct 2026

EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models

arXiv 2312.06281 ↗First posted 11 Dec 2023cs.CL cs.AIcited by 80

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Abstract (arXiv)

We introduce EQ-Bench, a novel benchmark designed to evaluate aspects of emotional intelligence in Large Language Models (LLMs). We assess the ability of LLMs to understand complex emotions and social interactions by asking them to predict the intensity of emotional states of characters in a dialogue. The benchmark is able to discriminate effectively between a wide range of models. We find that EQ-Bench correlates strongly with comprehensive multi-domain benchmarks like MMLU (Hendrycks et al., 2020) (r=0.97), indicating that we may be capturing similar aspects of broad intelligence. Our benchmark produces highly repeatable results using a set of 60 English-language questions. We also provide open-source code for an automated benchmarking pipeline at https://github.com/EQ-bench/EQ-Bench and a leaderboard at https://eqbench.com

Key facts. Cited by 80 papers in the map (data through 14 Oct 2026). Builds on 11 of its 23 references that are in the map. First posted on arXiv 11 Dec 2023.

Builds on

11 of 23 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  3. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
  4. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  6. 2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,100
  7. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  8. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
  9. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 681
  10. 20218-bit Optimizers via Block-wise Quantizationcited by 403
  11. 2023Emotional Intelligence of Large Language Modelscited by 58

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Citing papers per year: 2023: 1; 2024: 8; 2025: 34; 2026: 37.

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