INO is an index-time method that uses the production RAG agent to iteratively create, test with queries and paraphrases, reflect on failures, and revise factual nuggets until they are discoverable and used correctly.
Rag4tickets: Ai-powered ticket resolution via retrieval- augmented generation on jira and github data
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Retrieval-augmented generation reaches 0.66 weighted F1 for invalid bug report subclassification while agentic web search reaches 68.9% Judge LLM success for no-code fix generation.
citing papers explorer
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Iterate Until Retrieved: Factual Nugget Optimization for Discoverable Continual Corrections in Agentic RAG
INO is an index-time method that uses the production RAG agent to iteratively create, test with queries and paraphrases, reflect on failures, and revise factual nuggets until they are discoverable and used correctly.