ECHO stores each agent turn as a source-indexed memory, reconstructs bounded contexts by selecting useful records, and routes RL credit through the same selection trace — reaching 43.4% on BrowseComp-Plus vs 28.9% (GRPO) and 36.1% (SUPO).
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
AI claim verification models rely on salient-constraint shortcuts instead of full compositional reasoning under the closed-world assumption, as revealed by their over-acceptance of claims with supported salient constraints but contradicted non-salient ones.
Scaling the delegation backbone in hierarchical search agents improves EM by ~11 points while scaling the executor moves EM by only ~2.6 points, and a 1.7B SFT executor matches a frontier sub-agent at 37% fewer tokens.
citing papers explorer
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ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL
ECHO stores each agent turn as a source-indexed memory, reconstructs bounded contexts by selecting useful records, and routes RL credit through the same selection trace — reaching 43.4% on BrowseComp-Plus vs 28.9% (GRPO) and 36.1% (SUPO).
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When Verification Fails: How Compositionally Infeasible Claims Escape Rejection
AI claim verification models rely on salient-constraint shortcuts instead of full compositional reasoning under the closed-world assumption, as revealed by their over-acceptance of claims with supported salient constraints but contradicted non-salient ones.
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Think Big, Search Small: Where Capacity Matters in Hierarchical Search Agents?
Scaling the delegation backbone in hierarchical search agents improves EM by ~11 points while scaling the executor moves EM by only ~2.6 points, and a 1.7B SFT executor matches a frontier sub-agent at 37% fewer tokens.