arXiv Computation and Language
WARP: Wasserstein-Aligned RAG for Population Opinions
Read the original on arXiv Computation and Language →The Flow has not summarised this story yet — read it at arXiv Computation and Language.
Related stories
arXiv AI
Jun 6
Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions
arXiv:2604. 12138v2 Announce Type: replace Abstract: This position paper argues that Retrieval-Augmented Generation systems exhibit a systematic factual bias-optimizing for epistemic uncertainty reduction while ignoring the aleatoric uncertainty inherent in opinion-rich content - and that this misalignment demands a paradigm shift in retrieval system design.
arXiv AI
Jun 30
Beyond the Reranker: Do RAG Retrieval Enhancements Help Once a Strong Reranker Is Present?
arXiv:2606. 28367v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is routinely extended with methods meant to improve retrieval: query expansion, hierarchical and cross-document summarization, graph-based expansion, per-query routing, rank fusion, and corrective re-retrieval.
arXiv AI
Oct 27
Retriever-Free Retrieval: Navigating Documents with Decision Models
arXiv:2610.35868v1 Announce Type: new Abstract: While language models have become dramatically more capable, retrieval still largely relies on lexical matching or similarity in fixed embedding spaces...
arXiv Machine Learning
Sep 10
Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools
arXiv:2602.18613v2 Announce Type: replace Abstract: Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever. This setup couples ranking behavior with r...
Hugging Face Trending Papers
Oct 26
Retriever-Free Retrieval: Navigating Documents with Decision Models
While language models have become dramatically more capable, retrieval still largely relies on lexical matching or similarity in fixed embedding spaces. This creates a capability asymmetry: what the r...
arXiv Computation and Language
Oct 15
When More Documents Hurt RAG: Measuring and Reducing Vector Search Dilution with Domain-Scoped Retrieval
arXiv:2606.11350v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) degrades when applied to large, heterogeneous document collections. In RAG systems, dense similarity becomes l...