mlsanityData to 7 Oct 2026

StyEmp: Stylizing Empathetic Response Generation via Multi-Grained Prefix Encoder and Personality Reinforcement

arXiv 2408.02271 ↗First posted 5 Aug 2024cs.CLcited by 3

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Abstract (arXiv)

Recent approaches for empathetic response generation mainly focus on emotional resonance and user understanding, without considering the system's personality. Consistent personality is evident in real human expression and is important for creating trustworthy systems. To address this problem, we propose StyEmp, which aims to stylize the empathetic response generation with a consistent personality. Specifically, it incorporates a multi-grained prefix mechanism designed to capture the intricate relationship between a system's personality and its empathetic expressions. Furthermore, we introduce a personality reinforcement module that leverages contrastive learning to calibrate the generation model, ensuring that responses are both empathetic and reflective of a distinct personality. Automatic and human evaluations on the EMPATHETICDIALOGUES benchmark show that StyEmp outperforms competitive baselines in terms of both empathy and personality expressions.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 28 of its 47 references that are in the map. First posted on arXiv 5 Aug 2024.

Builds on

28 of 47 references.

References · 28

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  4. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  5. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  6. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  7. 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,068
  8. 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
  9. 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
  10. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  11. 2016Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Modelscited by 299
  12. 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
16 more
  1. 2022BRIO: Bringing Order to Abstractive Summarizationcited by 161
  2. 2018Training Millions of Personalized Dialogue Agentscited by 126
  3. 2020MIME: MIMicking Emotions for Empathetic Response Generationcited by 114
  4. 2021CEM: Commonsense-aware Empathetic Response Generationcited by 89
  5. 2022Same Author or Just Same Topic? Towards Content-Independent Style Representationscited by 83
  6. 2020A Taxonomy of Empathetic Response Intents in Human Social Conversationscited by 51
  7. 2022Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generationcited by 47
  8. 2021Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causescited by 43
  9. 2020PANDORA Talks: Personality and Demographics on Redditcited by 40
  10. 2023Aligning Language Models with Human Preferences via a Bayesian Approachcited by 27
  11. 2023RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generationcited by 25
  12. 2023Controlling Personality Style in Dialogue with Zero-Shot Prompt-Based Learningcited by 14
  13. 2021Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human Communicationcited by 9
  14. 2023DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generationcited by 9
  15. 2023Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generationcited by 9
  16. 2022CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generationcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.