mlsanityData to 7 Oct 2026

EmpBot: A T5-based Empathetic Chatbot focusing on Sentiments

arXiv 2111.00310 ↗First posted 30 Oct 2021cs.CL cs.AIcited by 5

Not on the map. Why?

Abstract (arXiv)

In this paper, we introduce EmpBot: an end-to-end empathetic chatbot. Empathetic conversational agents should not only understand what is being discussed, but also acknowledge the implied feelings of the conversation partner and respond appropriately. To this end, we propose a method based on a transformer pretrained language model (T5). Specifically, during finetuning we propose to use three objectives: response language modeling, sentiment understanding, and empathy forcing. The first objective is crucial for generating relevant and coherent responses, while the next ones are significant for acknowledging the sentimental state of the conversational partner and for favoring empathetic responses. We evaluate our model on the EmpatheticDialogues dataset using both automated metrics and human evaluation. The inclusion of the sentiment understanding and empathy forcing auxiliary losses favor empathetic responses, as human evaluation results indicate, comparing with the current state-of-the-art.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 35 of its 51 references that are in the map. First posted on arXiv 30 Oct 2021.

Builds on

35 of 51 references.

References · 35

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  3. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  4. 2018Hierarchical Neural Story Generationcited by 1,182
  5. 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,068
  6. 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
  7. 2020Recipes for building an open-domain chatbotcited by 593
  8. 2016How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generationcited by 356
  9. 2016Deep Reinforcement Learning for Dialogue Generationcited by 286
  10. 2016A Persona-Based Neural Conversation Modelcited by 221
  11. 2015A Neural Conversational Modelcited by 195
  12. 2019TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agentscited by 188
23 more
  1. 2019The Second Conversational Intelligence Challenge (ConvAI2)cited by 178
  2. 2016A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialoguescited by 174
  3. 2017Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memorycited by 167
  4. 2015Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systemscited by 134
  5. 2018Training Millions of Personalized Dialogue Agentscited by 126
  6. 2020MIME: MIMicking Emotions for Empathetic Response Generationcited by 114
  7. 2015A Neural Network Approach to Context-Sensitive Generation of Conversational Responsescited by 98
  8. 2019MoEL: Mixture of Empathetic Listenerscited by 91
  9. 2019Personalizing Dialogue Agents via Meta-Learningcited by 83
  10. 2018Retrieve and Refine: Improved Sequence Generation Models For Dialoguecited by 82
  11. 2015A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestioncited by 68
  12. 2017MojiTalk: Generating Emotional Responses at Scalecited by 64
  13. 2018Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memorycited by 49
  14. 2018Importance of Search and Evaluation Strategies in Neural Dialogue Modelingcited by 44
  15. 2018Response Generation by Context-aware Prototype Editingcited by 40
  16. 2017Personalization in Goal-Oriented Dialogcited by 28
  17. 2019DeepCopy: Grounded Response Generation with Hierarchical Pointer Networkscited by 22
  18. 2019CAiRE: An Empathetic Neural Chatbotcited by 14
  19. 2018Emo2Vec: Learning Generalized Emotion Representation by Multi-task Trainingcited by 11
  20. 2018Multi-Region Ensemble Convolutional Neural Network for Facial Expression Recognitioncited by 7
  21. 2018Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partnercited by 7
  22. 2019CAiRE_HKUST at SemEval-2019 Task 3: Hierarchical Attention for Dialogue Emotion Classificationcited by 3
  23. 2019A Simple Dual-decoder Model for Generating Response with Sentimentcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 2; 2025: 1; 2026: 1.

5 papers.

  1. 2022Empathetic Conversational Systems: A Review of Current Advances, Gaps, and Opportunitiescited by 14
  2. 2024ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion Modelingcited by 7
  3. 2024EmPO: Emotion Grounding for Empathetic Response Generation through Preference Optimizationcited by 3
  4. 2025Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactionscited by 3
  5. 2026Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversationcited by 1