mlsanityData to 7 Oct 2026

SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures

arXiv 2110.07518 ↗First posted 14 Oct 2021cs.CL cs.AIcited by 37

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Abstract (arXiv)

Current open-domain conversational models can easily be made to talk in inadequate ways. Online learning from conversational feedback given by the conversation partner is a promising avenue for a model to improve and adapt, so as to generate fewer of these safety failures. However, current state-of-the-art models tend to react to feedback with defensive or oblivious responses. This makes for an unpleasant experience and may discourage conversation partners from giving feedback in the future. This work proposes SaFeRDialogues, a task and dataset of graceful responses to conversational feedback about safety failures. We collect a dataset of 10k dialogues demonstrating safety failures, feedback signaling them, and a response acknowledging the feedback. We show how fine-tuning on this dataset results in conversations that human raters deem considerably more likely to lead to a civil conversation, without sacrificing engagingness or general conversational ability.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). Builds on 16 of its 34 references that are in the map. First posted on arXiv 14 Oct 2021.

Builds on

16 of 34 references.

References · 16

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  2. 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
  3. 2020Recipes for building an open-domain chatbotcited by 593
  4. 2020Towards a Human-like Open-Domain Chatbotcited by 467
  5. 2020The Pushshift Reddit Datasetcited by 289
  6. 2019Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attackcited by 176
  7. 2017ParlAI: A Dialog Research Software Platformcited by 139
  8. 2020Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skillscited by 130
  9. 2019Learning from Dialogue after Deployment: Feed Yourself, Chatbot!cited by 102
  10. 2019ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisonscited by 83
  11. 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 77
  12. 2021Generate, Prune, Select: A Pipeline for Counterspeech Generation against Online Hate Speechcited by 42
4 more
  1. 2020Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directionscited by 34
  2. 2020Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversationscited by 24
  3. 2019A Crowd-based Evaluation of Abuse Response Strategies in Conversational Agentscited by 12
  4. 2021Countering Online Hate Speech: An NLP Perspectivecited by 12

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 9; 2024: 14; 2025: 3; 2026: 2.

37 papers.

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  1. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  2. 2023Bias and Fairness in Large Language Models: A Surveycited by 626
  3. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  4. 2024Attacks, Defenses and Evaluations for LLM Conversation Safety: A Surveycited by 124
  5. 2022ProsocialDialog: A Prosocial Backbone for Conversational Agentscited by 109
  6. 2024Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Eracited by 97
  7. 2024SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safetycited by 75
  8. 2024CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreferencecited by 51
  9. 2023Using In-Context Learning to Improve Dialogue Safetycited by 41
  10. 2022InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuningcited by 39
  11. 2022Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarkscited by 36
  12. 2022Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbotscited by 31
25 more
  1. 2023Ask an Expert: Leveraging Language Models to Improve Strategic Reasoning in Goal-Oriented Dialogue Modelscited by 30
  2. 2023Safer-Instruct: Aligning Language Models with Automated Preference Datacited by 27
  3. 2024NLP for Counterspeech against Hate: A Survey and How-To Guidecited by 21
  4. 2023Which Prompts Make The Difference? Data Prioritization For Efficient Human LLM Evaluationcited by 18
  5. 2023Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?cited by 7
  6. 2024Mitigating Social Biases in Language Models through Unlearningcited by 7
  7. 2026VerifyMAS: Hypothesis Verification for Failure Attribution in LLM Multi-Agent Systemscited by 5
  8. 2024Purple-teaming LLMs with Adversarial Defender Trainingcited by 4
  9. 2024Weak-to-Strong Generalization beyond Accuracy: a Pilot Study in Safety, Toxicity, and Legal Reasoningcited by 4
  10. 2025Guarding the Guardrails: A Taxonomy-Driven Approach to Jailbreak Detectioncited by 4
  11. 2022DialGuide: Aligning Dialogue Model Behavior with Developer Guidelinescited by 3
  12. 2023Effortless Integration of Memory Management into Open-Domain Conversation Systemscited by 3
  13. 2023CESAR: Automatic Induction of Compositional Instructions for Multi-turn Dialogscited by 3
  14. 2024Learning from Implicit User Feedback, Emotions and Demographic Information in Task-Oriented and Document-Grounded Dialoguescited by 3
  15. 2024The Life Cycle of Large Language Models: A Review of Biases in Educationcited by 3
  16. 2024Chained Tuning Leads to Biased Forgettingcited by 3
  17. 2022Bipartite-play Dialogue Collection for Practical Automatic Evaluation of Dialogue Systemscited by 1
  18. 2022Sources of Noise in Dialogue and How to Deal with Themcited by 1
  19. 2023Healing Unsafe Dialogue Responses with Weak Supervision Signalscited by 1
  20. 2024GrounDial: Human-norm Grounded Safe Dialog Response Generationcited by 1
  21. 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Modelscited by 1
  22. 2024Improving Dialog Safety using Socially Aware Contrastive Learningcited by 0
  23. 2025Towards Automated Error Discovery: A Study in Conversational AIcited by 0
  24. 2025CTIGuardian: A Few-Shot Framework for Mitigating Privacy Leakage in Fine-Tuned LLMscited by 0
  25. 2026RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generationcited by 0