mlsanityData to 7 Oct 2026

DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversations

arXiv 2310.11374 ↗First posted 17 Oct 2023cs.CLcited by 29

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Abstract (arXiv)

Large language models (LLMs) and their variants have shown extraordinary efficacy across numerous downstream natural language processing (NLP) tasks, which has presented a new vision for the development of NLP. Despite their remarkable performance in natural language generating (NLG), LLMs lack a distinct focus on the emotion understanding domain. As a result, using LLMs for emotion recognition may lead to suboptimal and inadequate precision. Another limitation of LLMs is that they are typical trained without leveraging multi-modal information. To overcome these limitations, we propose DialogueLLM, a context and emotion knowledge tuned LLM that is obtained by fine-tuning LLaMA models with 13,638 multi-modal (i.e., texts and videos) emotional dialogues. The visual information is considered as the supplementary knowledge to construct high-quality instructions. We offer a comprehensive evaluation of our proposed model on three benchmarking emotion recognition in conversations (ERC) datasets and compare the results against the SOTA baselines and other SOTA LLMs. Additionally, DialogueLLM-7B can be easily trained using LoRA on a 40GB A100 GPU in 5 hours, facilitating reproducibility for other researchers.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 29 of its 61 references that are in the map. First posted on arXiv 17 Oct 2023.

Builds on

29 of 61 references.

References · 29

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2023The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Onlycited by 755
  6. 2018MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversationscited by 636
  7. 2023ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledgecited by 324
  8. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 262
  9. 2018DialogueRNN: An Attentive RNN for Emotion Detection in Conversationscited by 216
  10. 2019DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversationcited by 184
  11. 2023Large Language Models Understand and Can be Enhanced by Emotional Stimulicited by 143
  12. 2017Emotion Detection on TV Show Transcripts with Sequence-based Convolutional Neural Networkscited by 102
17 more
  1. 2021Directed Acyclic Graph Network for Conversational Emotion Recognitioncited by 97
  2. 2023Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Taskscited by 84
  3. 2020DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognitioncited by 78
  4. 2022A Survey of Knowledge Enhanced Pre-trained Language Modelscited by 76
  5. 2021DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversationscited by 71
  6. 2022A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challengescited by 61
  7. 2022UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognitioncited by 61
  8. 2021Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detectioncited by 56
  9. 2021Multimodal Learning using Optimal Transport for Sarcasm and Humor Detectioncited by 36
  10. 2021Contrast and Generation Make BART a Good Dialogue Emotion Recognizercited by 35
  11. 2022COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognitioncited by 22
  12. 2022GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognitioncited by 20
  13. 2023Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversationscited by 19
  14. 2021Variational Latent-State GPT for Semi-Supervised Task-Oriented Dialog Systemscited by 13
  15. 2020Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognitioncited by 12
  16. 2022Multitask Learning from Augmented Auxiliary Data for Improving Speech Emotion Recognitioncited by 11
  17. 2023A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysiscited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 11; 2025: 13; 2026: 4.

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  1. 2024A Survey on LoRA of Large Language Modelscited by 67
  2. 2024EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysiscited by 62
  3. 2024Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thoughtcited by 34
  4. 2024VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoningcited by 15
  5. 2024Large Vision-Language Models as Emotion Recognizers in Context Awarenesscited by 12
  6. 2024Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligencecited by 11
  7. 2023The Good, The Bad, and Why: Unveiling Emotions in Generative AIcited by 10
  8. 2025Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospectscited by 10
  9. 2025Decoding Emotion in the Deep: A Systematic Study of How LLMs Represent, Retain, and Express Emotioncited by 10
  10. 2025Large Language Models for Subjective Language Understanding: A Surveycited by 9
  11. 2025EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Modelscited by 5
  12. 2024Training A Small Emotional Vision Language Model for Visual Art Comprehensioncited by 4
17 more
  1. 2024Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversationcited by 3
  2. 2024Recognizing Emotion Regulation Strategies from Human Behavior with Large Language Modelscited by 3
  3. 2024Evaluating Large Language Models on Financial Report Summarization: An Empirical Studycited by 3
  4. 2025Chart-to-Experience: Benchmarking Multimodal LLMs for Predicting Experiential Impact of Chartscited by 3
  5. 2025Are MLMs Trapped in the Visual Room?cited by 2
  6. 2025When LLMs Team Up: The Emergence of Collaborative Affective Computingcited by 2
  7. 2026Towards Next-Generation Healthcare: A Survey of Medical Embodied AI for Perception, Decision-Making, and Actioncited by 2
  8. 2025Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion Classificationcited by 1
  9. 2024CAPE: A Chinese Dataset for Appraisal-based Emotional Generation using Large Language Modelscited by 0
  10. 2025BeMERC: Behavior-Aware MLLM-based Framework for Multimodal Emotion Recognition in Conversationcited by 0
  11. 2025Following the TRACE: A Structured Path to Empathetic Response Generation with Multi-Agent Modelscited by 0
  12. 2025Unraveling Emotions with Pre-Trained Modelscited by 0
  13. 2025DialogGraph-LLM: Graph-Informed LLMs for End-to-End Audio Dialogue Intent Recognitioncited by 0
  14. 2025A Customer Journey in the Land of Oz: Leveraging the Wizard of Oz Technique to Model Emotions in Customer Service Interactionscited by 0
  15. 2026Large language models for spreading dynamics in complex systemscited by 0
  16. 2026A Hormone-inspired Emotion Layer for Transformer language models (HELT)cited by 0
  17. 2026VISAFF: Speaker-Centered Visual Affective Feature Learning for Emotion Recognition in Conversationcited by 0