mlsanityData to 7 Oct 2026

Human-like Affective Cognition in Foundation Models

arXiv 2409.11733 ↗First posted 18 Sep 2024cs.CLcited by 13

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Abstract (arXiv)

Understanding emotions is fundamental to human interaction and experience. Humans easily infer emotions from situations or facial expressions, situations from emotions, and do a variety of other affective cognition. How adept is modern AI at these inferences? We introduce an evaluation framework for testing affective cognition in foundation models. Starting from psychological theory, we generate 1,280 diverse scenarios exploring relationships between appraisals, emotions, expressions, and outcomes. We evaluate the abilities of foundation models (GPT-4, Claude-3, Gemini-1.5-Pro) and humans (N = 567) across carefully selected conditions. Our results show foundation models tend to agree with human intuitions, matching or exceeding interparticipant agreement. In some conditions, models are ``superhuman'' -- they better predict modal human judgements than the average human. All models benefit from chain-of-thought reasoning. This suggests foundation models have acquired a human-like understanding of emotions and their influence on beliefs and behavior.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 20 of its 48 references that are in the map. First posted on arXiv 18 Sep 2024.

Builds on

20 of 48 references.

References · 20

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  5. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  6. 2022Red Teaming Language Models with Language Modelscited by 983
  7. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 805
  8. 2018Deep Facial Expression Recognition: A Surveycited by 269
  9. 2023Understanding Social Reasoning in Language Models with Language Modelscited by 166
  10. 2021Understanding the Capabilities, Limitations, and Societal Impact of Large Language Modelscited by 159
  11. 2018Deep Learning for Sentiment Analysis : A Surveycited by 139
  12. 2022Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Supportcited by 68
8 more
  1. 2024Large Language Models Produce Responses Perceived to be Empathiccited by 36
  2. 2023Fine-grained Affective Processing Capabilities Emerging from Large Language Modelscited by 24
  3. 2024GPT-4 Emulates Average-Human Emotional Cognition from a Third-Person Perspectivecited by 16
  4. 2024Large Language Models are Capable of Offering Cognitive Reappraisal, if Guidedcited by 13
  5. 2023Investigating Large Language Models' Perception of Emotion Using Appraisal Theorycited by 12
  6. 2023Evaluating Subjective Cognitive Appraisals of Emotions from Large Language Modelscited by 12
  7. 2021An Ethical Framework for Guiding the Development of Affectively-Aware Artificial Intelligencecited by 4
  8. 2024Procedural Dilemma Generation for Evaluating Moral Reasoning in Humans and Language Modelscited by 4

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Citing papers per year: 2025: 5; 2026: 8.

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  1. 2026Large Language Model Reasoning Failurescited by 20
  2. 2026HEART: A Unified Benchmark for Assessing Humans and LLMs in Emotional Support Dialoguecited by 12
  3. 2025Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applicationscited by 10
  4. 2026Learning to Simulate Human Dialoguecited by 9
  5. 2025Emergence of Hierarchical Emotion Organization in Large Language Modelscited by 6
  6. 2025Retrieval-augmented systems can be dangerous medical communicatorscited by 5
  7. 2025Metacognitive Sensitivity for Test-Time Dynamic Model Selectioncited by 2
  8. 2026Scaling Ambiguity: Augmenting Human Annotation in Speech Emotion Recognition with Audio-Language Modelscited by 2
  9. 2026CAREBench: Evaluating LLMs' Emotion Understanding by Assessing Cognitive Appraisal Reasoningcited by 2
  10. 2025An Affective-Taxis Hypothesis for Alignment and Interpretabilitycited by 1
  11. 2026Do LLMs Share Human-Like Biases? Causal Reasoning Under Prior Knowledge, Irrelevant Context, and Varying Compute Budgetscited by 1
  12. 2026CBMAS: Cognitive Behavioral Modeling via Activation Steeringcited by 0
1 more
  1. 2026Visual Affect Analysis: Predicting Emotions of Image Viewers with Vision-Language Modelscited by 0

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  1. 2025Large language models show fragile cognitive reasoning about human emotions
  2. 2023The Good, The Bad, and Why: Unveiling Emotions in Generative AI
  3. 2025Artificial Intelligence Can Emulate Human Normative Judgments on Emotional Visual Scenes ↗
  4. 2025Beyond Context to Cognitive Appraisal: Emotion Reasoning as a Theory of Mind Benchmark for Large Language Models
  5. 2025Reading Smiles: Proxy Bias in Foundation Models for Facial Emotion Recognition
  6. 2026Psychological Competence as a Missing Dimension in AI Evaluation
  7. 2026Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans
  8. 2025Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models