A Cornell paper, summarized in Chinese by @shao__meng, uses the Jev decision model to decide layer by layer which topics, documents and passages to expand, scoring candidates together in one forward pass without a vector index. The post reports R@1 13.8 po...
VQV Signal
RESEARCH
WATCH
TECHNICAL
DecisionRAG: retrieval with no retriever, using a decision model to walk a document tree
A Cornell paper, summarized in Chinese by @shao__meng, uses the Jev decision model to decide layer by layer which topics, documents and passages to expand, scoring candidates together in one forward pass without a vector index. The post reports R@1 13.8 po...
A Cornell paper, summarized in Chinese by @shao__meng, uses the Jev decision model to decide layer by layer which topics, documents and passages to expand, scoring candidates together in one forward pass without a vector index. The post reports R@1 13.8 points above dense retrieval plus an 8B reranker on...
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Signal Strength 91%
Technical label WATCH
Public Interest 21
Category RESEARCH
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 0
Practical Impact Score 0
Novelty Interest Score 70
Consequence Score 18
Curiosity Score 0
Shareability Score 41
Topics
VQV surfaced this signal because it is recent, relevant to AI Search, connected to Scobleizer News Pulse (X).
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