arXiv (All)
open access
WARP: Wasserstein-Aligned RAG for Population Opinions
RAG systems are increasingly used to summarize what large collections of documents say. A user asks "What do people think about X?" and receives an answer that reads as consensus. But standard top-k retrieval ranks documents by query similarity, not by how faithfully they represent the population, s
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
- Exploration of Intrinsic Relevance Judgments by Legal Professionals in Information Retrieval Systems#279135
- A DEMPSTER-SHAFER MODEL OF RELEVANCE#933548
- Measuring the drafting alignment of patent documents using text mining#163507
- TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems#925721
- A Living Benchmark for Information Retrieval from Electronic Health Records#1078276
Record · ID 1062989
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