Pi-Serini shows a tuned BM25 lexical retriever with adequate depth, used inside an LLM agentic loop, reaches 83.1% accuracy and 94.7% evidence recall on BrowseComp-Plus while beating released dense-retriever agents.
Keep it specific, under 100 words, and focused on the clue, gap, candidate, or ranking issue
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Rethinking Agentic Search with Pi-Serini: Is Lexical Retrieval Sufficient?
Pi-Serini shows a tuned BM25 lexical retriever with adequate depth, used inside an LLM agentic loop, reaches 83.1% accuracy and 94.7% evidence recall on BrowseComp-Plus while beating released dense-retriever agents.