mlsanityData to 14 Oct 2026

Large Language Models Understand and Can be Enhanced by Emotional Stimuli

arXiv 2307.11760 ↗First posted 14 Jul 2023cs.CL cs.AI cs.HCcited by 146

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Abstract (arXiv)

Emotional intelligence significantly impacts our daily behaviors and interactions. Although Large Language Models (LLMs) are increasingly viewed as a stride toward artificial general intelligence, exhibiting impressive performance in numerous tasks, it is still uncertain if LLMs can genuinely grasp psychological emotional stimuli. Understanding and responding to emotional cues gives humans a distinct advantage in problem-solving. In this paper, we take the first step towards exploring the ability of LLMs to understand emotional stimuli. To this end, we first conduct automatic experiments on 45 tasks using various LLMs, including Flan-T5-Large, Vicuna, Llama 2, BLOOM, ChatGPT, and GPT-4. Our tasks span deterministic and generative applications that represent comprehensive evaluation scenarios. Our automatic experiments show that LLMs have a grasp of emotional intelligence, and their performance can be improved with emotional prompts (which we call "EmotionPrompt" that combines the original prompt with emotional stimuli), e.g., 8.00% relative performance improvement in Instruction Induction and 115% in BIG-Bench. In addition to those deterministic tasks that can be automatically evaluated using existing metrics, we conducted a human study with 106 participants to assess the quality of generative tasks using both vanilla and emotional prompts. Our human study results demonstrate that EmotionPrompt significantly boosts the performance of generative tasks (10.9% average improvement in terms of performance, truthfulness, and responsibility metrics). We provide an in-depth discussion regarding why EmotionPrompt works for LLMs and the factors that may influence its performance. We posit that EmotionPrompt heralds a novel avenue for exploring interdisciplinary knowledge for human-LLMs interaction.

Key facts. Cited by 146 papers in the map (data through 14 Oct 2026). Builds on 17 of its 40 references that are in the map. First posted on arXiv 14 Jul 2023.

Builds on

17 of 40 references.

References · 17

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  5. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  6. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  7. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
  8. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  9. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
  10. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,984
  11. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,807
  12. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
5 more
  1. 2023Large Language Modelscited by 780
  2. 2022A Survey on In-context Learningcited by 721
  3. 2022What Can Transformers Learn In-Context? A Case Study of Simple Function Classescited by 715
  4. 2023PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Promptscited by 226
  5. 2022Instruction Induction: From Few Examples to Natural Language Task Descriptionscited by 152

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Citing papers per year: 2023: 7; 2024: 55; 2025: 43; 2026: 41.

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  1. 2024A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applicationscited by 431
  2. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 126
  3. 2024PsySafe: A Comprehensive Framework for Psychological-based Attack, Defense, and Evaluation of Multi-agent System Safetycited by 80
  4. 2024LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Playcited by 66
  5. 2025A Systematic Survey of Automatic Prompt Optimization Techniquescited by 63
  6. 2024A Computational Framework for Behavioral Assessment of LLM Therapistscited by 62
  7. 2024Do LLMs Know When to NOT Answer? Investigating Abstention Abilities of Large Language Modelscited by 57
  8. 2026Emotion Concepts and their Function in a Large Language Modelcited by 57
  9. 2023Emotionally Numb or Empathetic? Evaluating How LLMs Feel Using EmotionBenchcited by 54
  10. 2024EmoBench: Evaluating the Emotional Intelligence of Large Language Modelscited by 53
  11. 2024Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)cited by 46
  12. 2025Infrastructure for AI Agentscited by 41
38 more
  1. 2024CoMM: Collaborative Multi-Agent, Multi-Reasoning-Path Prompting for Complex Problem Solvingcited by 31
  2. 2023DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversationscited by 30
  3. 2024SPRIG: Improving Large Language Model Performance by System Prompt Optimizationcited by 29
  4. 2024Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machinacited by 29
  5. 2024Foot In The Door: Understanding Large Language Model Jailbreaking via Cognitive Psychologycited by 27
  6. 2024Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuancescited by 27
  7. 2024Human-like object concept representations emerge naturally in multimodal large language modelscited by 25
  8. 2024MMREC: LLM Based Multi-Modal Recommender Systemcited by 22
  9. 2024I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBenchcited by 21
  10. 2024A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Changecited by 21
  11. 2026Brittlebench: Quantifying LLM robustness via prompt sensitivitycited by 21
  12. 2024The Potential and Challenges of Evaluating Attitudes, Opinions, and Values in Large Language Modelscited by 19
  13. 2025Evaluating Vision-Language Models for Emotion Recognitioncited by 19
  14. 2024Causal Evaluation of Language Modelscited by 18
  15. 2024Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewingcited by 17
  16. 2024Walking in Others' Shoes: How Perspective-Taking Guides Large Language Models in Reducing Toxicity and Biascited by 17
  17. 2024PrExMe! Large Scale Prompt Exploration of Open Source LLMs for Machine Translation and Summarization Evaluationcited by 16
  18. 2025Evaluating the Goal-Directedness of Large Language Modelscited by 16
  19. 2026Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Controlcited by 16
  20. 2024From Imitation to Introspection: Probing Self-Consciousness in Language Modelscited by 14
  21. 2024The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysiscited by 13
  22. 2025Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluationcited by 13
  23. 2025Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey Responsescited by 13
  24. 2024Do Prompts Really Prompt? Exploring the Prompt Understanding Capability of Whispercited by 12
  25. 2025Affective Image Editing: Shaping Emotional Factors via Text Descriptionscited by 12
  26. 2025Decoding Emotion in the Deep: A Systematic Study of How LLMs Represent, Retain, and Express Emotioncited by 12
  27. 2026PERSONA: Dynamic and Compositional Inference-Time Personality Control via Activation Vector Algebracited by 12
  28. 2024Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspectivecited by 11
  29. 2024Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligencecited by 11
  30. 2025AI with Emotions: Exploring Emotional Expressions in Large Language Modelscited by 11
  31. 2023The Good, The Bad, and Why: Unveiling Emotions in Generative AIcited by 10
  32. 2024Mirror: A Multiple-perspective Self-Reflection Method for Knowledge-rich Reasoningcited by 10
  33. 2025Do Large Language Models Understand Word Senses?cited by 10
  34. 2024Guiding Enumerative Program Synthesis with Large Language Modelscited by 9
  35. 2024Measuring Psychological Depth in Language Modelscited by 9
  36. 2024DisasterQA: A Benchmark for Assessing the performance of LLMs in Disaster Responsecited by 9
  37. 2025Bandit-Based Prompt Design Strategy Selection Improves Prompt Optimizerscited by 9
  38. 2025Emergence of Hierarchical Emotion Organization in Large Language Modelscited by 9

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