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Debate-to-Skill: Capability-Bound Process Supervision for Industrial Query-to-Agent Annotation

arXiv 2609.11176 ↗First posted 10 Sep 2026cs.AIcited by 0

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Abstract (arXiv)

Industrial query-to-agent matching fails when topical relevance is mistaken for executable capability, especially on long-tail and boundary-sensitive requests. We formulate annotation as capability-bound process supervision and instantiate it with Debate-to-Skill, which uses reusable decision principles, structured deliberation, verifier-based verdict extraction, and disagreement-driven refinement. On an industrial Query2Agent benchmark, we compare Debate-to-Skill with direct-label supervision, reasoning-SFT, and structural ablations. The results test whether gains come from supervising the capability-critical decision process itself, especially on grey-zone cases where semantic relatedness and executable capability diverge.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 30 references that are in the map. First posted on arXiv 10 Sep 2026.

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References · 22

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2023Let's Verify Step by Stepcited by 3,789
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  6. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  7. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  8. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
  9. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,407
  10. 2025A-MEM: Agentic Memory for LLM Agentscited by 1,063
  11. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMscited by 591
  12. 2023Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervisioncited by 467
10 more
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  2. 2026SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalizationcited by 94
  3. 2025Great Models Think Alike and this Undermines AI Oversightcited by 58
  4. 2026Dynamic Dual-Granularity Skill Bank for Agentic RLcited by 34
  5. 2024Weak-to-Strong Generalization Through the Data-Centric Lenscited by 21
  6. 2026SKILLC: Learning Autonomous Skill Internalization in LLM Agents via Contrastive Credit Assignmentcited by 9
  7. 2026Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learningcited by 9
  8. 2024Bayesian WeakS-to-Strong from Text Classification to Generationcited by 6
  9. 2026Scaling Agentic Capabilities, Not Context: Efficient Reinforcement Finetuning for Large Toolspacescited by 4
  10. 2026Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generationcited by 1

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