arXiv (OAI Expanded)
open access
EviQE: Evidence Selection for LLM-Based Query Expansion
LLM-based query expansion increasingly conditions reformulation on documents retrieved from the target corpus, yet most work focuses on how to generate expansions rather than which documents the model should read. We propose EviQE, which aggregates documents retrieved by multiple reformulators, sele
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
- Socrates-RAG: Premise-Directed Inquiry against Coordinated Evidence Poisoning#1130615
- A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly#1135303
- Hypothesis Generation with Large Language Models#328720
- Automated Generation of Massive Reasonable Empirical Theorems by Forward Reasoning Based on Strong Relevant Logics - A Solution to the Problem of LLM Pre-training Data Exhaustion#689385
- Provenance Before Prose: Claim-Locked Reporting for Statistical Text Generation#1036765
Record · ID 1084788
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