SPIN Unprocessed October 23, 2026 ai_technology research
A Small Model Asks Better: Fine-Tuning Query Clarification for Retrieval-Augmented Generation
View original on arxiv.orgOverview
arXiv:2610.28686v1 Announce Type: new Abstract: Query clarification is essential for retrieval-augmented generation (RAG) systems that face ambiguous user queries. We consider multi-turn grounded conversational scenarios where a user query is either ill-formed or ambiguous in the context of the prior dialog or, more interestingly, it may be well-formed but when posed against retrieved documents there are multiple relevant interpretations. The task is to recognize both such cases and then generat
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Artificial Intelligence
View all →- An Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning
- AgentPolicyForge: From Executable Environments to Policy Benchmarks and Adaptive Guards
- PerMIT: Securing Persistent Memory for LLM Agents via Machine-Checked Integrity Theorems and Scalable Community Trust
- Behavior Beyond Text: Evaluating Refusal Transfer Failure in LLM Agents
- Self-Improving Agents with World Model Predictive Paths
- Back Up Before You Regret: Measuring Backup Awareness and Automating Backup in Coding Agents
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO