arXiv (All)
open access
ACARE: Agent-Context-Aware Reranker for Iterative Search
In agentic search, a document can match an agent-generated sub-query without helping answer the user's original question. Conventional rerankers score documents against the sub-query alone, overlooking the broader task and the agent's reasoning. We introduce the Agent-Context-Aware Reranker (ACARe),
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Benchmarking and Training Reward Models for Cross-Source Evidence Grounding in Search Agents#1343033
- ITER: Interaction-Aware Retrieval for Agentic Search#998360
- CiteGuard-RAG: A Validation-Centered AI System for Evidence-Grounded Question Answering#1109870
- Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations#432562
- AtomRec: Evolving Atomic Memory for Agentic Recommendation#971543
Record · ID 1466874
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive