mlsanityData to 7 Oct 2026

Towards a Progression-Aware Autonomous Dialogue Agent

arXiv 2205.03692 ↗First posted 7 May 2022cs.CL cs.AIcited by 7

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Recent advances in large-scale language modeling and generation have enabled the creation of dialogue agents that exhibit human-like responses in a wide range of conversational scenarios spanning a diverse set of tasks, from general chit-chat to focused goal-oriented discourse. While these agents excel at generating high-quality responses that are relevant to prior context, they suffer from a lack of awareness of the overall direction in which the conversation is headed, and the likelihood of task success inherent therein. Thus, we propose a framework in which dialogue agents can evaluate the progression of a conversation toward or away from desired outcomes, and use this signal to inform planning for subsequent responses. Our framework is composed of three key elements: (1) the notion of a "global" dialogue state (GDS) space, (2) a task-specific progression function (PF) computed in terms of a conversation's trajectory through this space, and (3) a planning mechanism based on dialogue rollouts by which an agent may use progression signals to select its next response.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 23 of its 54 references that are in the map. First posted on arXiv 7 May 2022.

Builds on

23 of 54 references.

References · 23

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11 more
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Built on by

Cited by year (2026 to 7 Oct)

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

7 papers.

  1. 2023COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goalcited by 18
  2. 2024The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trendscited by 11
  3. 2024ORCHID: A Chinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarizationcited by 6
  4. 2025PARL-MT: Learning to Call Functions in Multi-Turn Conversation with Progress Awarenesscited by 4
  5. 2023Towards a Neural Era in Dialogue Management for Collaboration: A Literature Surveycited by 3
  6. 2026Human Label Variation in Implicit Discourse Relation Recognitioncited by 0
  7. 2026Beyond Direct Answering: Aligning Educational LLMs as Socratic Guides via Heuristic Reinforcement Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026ATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systems
  2. 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
  3. 2026Context-Agent: Dynamic Discourse Trees for Non-Linear Dialogue
  4. 2025PRINCIPLES: Synthetic Strategy Memory for Proactive Dialogue Agents
  5. 2025From What to Respond to When to Respond: Timely Response Generation for Open-domain Dialogue Agents
  6. 2023Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systems
  7. 2024Large Language Models as User-Agents for Evaluating Task-Oriented-Dialogue Systems
  8. 2024Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations