What is it about?
We built SIM-RAG, a smarter AI search helper that knows when it has enough info and when to keep looking. It “practices” multi-step searching on its own, learns from success and failure, and answers more accurately without needing expensive human training.
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Why is it important?
AI systems are now widely used to search for and combine information, but they often over-search, waste resources, or give wrong answers when unsure. With growing demand for efficient, accurate AI, our work offers a timely way to make these systems smarter and more reliable, without expensive training or data.
Perspectives
"Wisdom is knowing what you don't know" -Socrates Working on this paper was exciting because it tackles a gap I’ve seen firsthand in AI research—systems that don’t know when to stop searching. I hope SIM-RAG sparks new ways of building AI that are not only smarter and more efficient, but also more self-aware.
Linda Zeng
Read the Original
This page is a summary of: Knowing You Don't Know: Learning When to Continue Search in Multi-round RAG through Self-Practicing, July 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3726302.3730018.
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Contributors
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