Tencent’s RARG guides agentic search with relevance scores instead of top-k only
_reachsumit · x · 2026-07-28
Tencent researchers propose RARG, a relevance-aware search agent that uses retrieval scores as an execution prior for corpus interaction. Instead of only selecting top-k passages, it orders ripgrep-style traversal to expose relevant clues earlier, seeds promising entry points with query-relevant paragraphs, and reranks grep hits to surface informative excerpts. The paper reports better accuracy-efficiency tradeoffs on browse QA and reasoning-heavy retrieval tasks.
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