RESEARCHInvestigateNEXT 12 MONTHS
Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers proposed an Evaluation Agent middleware to detect knowledge poisoning and factual inaccuracies in RAG retrieval outputs.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 5 November 2026
- Collected by OneBench
- 25 Aug 2026, 03:04 UK
Stored source excerpt
arXiv:2608.21095v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they retrieve,…
Short excerpt from the collected text, not the full source. Use the source link to read it in context.
The factual summary is a OneBench synthesis, not a quotation or independent verification. Collection time is not publication time. Open the source for its full context; related reporting can share the same underlying announcement.