mlsanityData to 13 Oct 2026

Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation

arXiv 2310.07397 ↗First posted 11 Oct 2023cs.CL cs.AIcited by 23

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Abstract (arXiv)

Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI. In this work, by formulating a <dialogue act, topic> pair as the conversation target, we explore a novel problem of personalized target-oriented dialogue by considering personalization during the target accomplishment process. However, there remains an emergent need for high-quality datasets, and building one from scratch requires tremendous human effort. To address this, we propose an automatic dataset curation framework using a role-playing approach. Based on this framework, we construct a large-scale personalized target-oriented dialogue dataset, TopDial, which comprises about 18K multi-turn dialogues. The experimental results show that this dataset is of high quality and could contribute to exploring personalized target-oriented dialogue.

Key facts. Cited by 23 papers in the map (data through 13 Oct 2026). Builds on 22 of its 41 references that are in the map. First posted on arXiv 11 Oct 2023.

Builds on

22 of 41 references.

References · 22

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,231
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,072
  3. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
  4. 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
  5. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 478
  6. 2019Queens are Powerful too: Mitigating Gender Bias in Dialogue Generationcited by 152
  7. 2020Towards Topic-Guided Conversational Recommender Systemcited by 94
  8. 2019Proactive Human-Machine Conversation with Explicit Conversation Goalscited by 88
  9. 2019ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisonscited by 83
  10. 2019Target-Guided Open-Domain Conversationcited by 66
  11. 2023A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospectscited by 66
  12. 2022Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generationcited by 47
10 more
  1. 2021DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendationcited by 46
  2. 2021OTTers: One-turn Topic Transitions for Open-Domain Dialoguecited by 29
  3. 2020Keyword-Guided Neural Conversational Modelcited by 21
  4. 2020Dynamic Knowledge Routing Network For Target-Guided Open-Domain Conversationcited by 15
  5. 2018Controlling Personality-Based Stylistic Variation with Neural Natural Language Generatorscited by 14
  6. 2023Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialoguecited by 14
  7. 2022BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasetscited by 13
  8. 2022Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentationcited by 8
  9. 2023You Truly Understand What I Need: Intellectual and Friendly Dialogue Agents grounding Knowledge and Personacited by 8
  10. 2019Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialoguecited by 3

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 6; 2025: 11; 2026: 6.

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  1. 2025A Survey of Personalization: From RAG to Agentcited by 27
  2. 2024A Survey on Recent Advances in Conversational Data Generationcited by 23
  3. 2025Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutorscited by 18
  4. 2024Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrievalcited by 14
  5. 2024ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agentscited by 12
  6. 2024Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialoguecited by 11
  7. 2024The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trendscited by 11
  8. 2025ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agentscited by 9
  9. 2025CarMem: Enhancing Long-Term Memory in LLM Voice Assistants through Category-Boundingcited by 8
  10. 2024AutoPal: Autonomous Adaptation to Users for Personal AI Companionshipcited by 6
  11. 2025Towards Personalized Conversational Sales Agents: Contextual User Profiling for Strategic Actioncited by 6
  12. 2025Multi-Party Conversational Agents: A Surveycited by 6
11 more
  1. 2025ConsistentChat: Building Skeleton-Guided Consistent Multi-Turn Dialogues for Large Language Models from Scratchcited by 5
  2. 2026Data Selection for Multi-turn Dialogue Instruction Tuningcited by 4
  3. 2025PEToolLLM: Towards Personalized Tool Learning in Large Language Modelscited by 3
  4. 2025Enhancing Goal-oriented Proactive Dialogue Systems via Consistency Reflection and Correctioncited by 2
  5. 2026Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluationcited by 2
  6. 2025IP-Dialog: Evaluating Implicit Personalization in Dialogue Systems with Synthetic Datacited by 1
  7. 2026A Concise Agent is Less Expert: Revealing Side Effects of Using Style Features on Conversational Agentscited by 1
  8. 2025Planning with Diffusion Models for Target-Oriented Dialogue Systemscited by 0
  9. 2026SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selectioncited by 0
  10. 2026Beyond Model Scaling: Test-Time Intervention for Efficient Deep Reasoningcited by 0
  11. 2026ATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systemscited by 0