Retrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation

4 days agoReported by arXiv21

Retrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation. The story centres on RAG. Reported by arXiv. Bharat Hunt files it under AI Regulation and AI Models — the section covering law, policy, courts, standards and government positions on AI.

Written by Bharat Hunt from the headline and the coverage below. The original reporting is the source of truth.

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RAGtopic

Reported by arXiv

First seen 4 days ago

arXivRetrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation4 days agoChenjie Qiu

AI Hardware24

SANTA++: Sampling Attention through Representative Keys

SANTA++: Sampling Attention through Representative Keys. It centres on RAG, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Hardware — the section covering chips, accelerators, data centres, on-device inference and supply. Open the original report for the full detail.

arXiv28 Sept 2026

AI Research23

RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems

RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems. It centres on RAG, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.

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Retrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation

Companies, models and people in this story

Reported by arXiv

SANTA++: Sampling Attention through Representative Keys

RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems

UNREAL: Unifying Retrieval and Long-Context with a Single Model

Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents

Companies, models and people in this story

Reported by arXiv

Related AI coverage

SANTA++: Sampling Attention through Representative Keys

RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems

UNREAL: Unifying Retrieval and Long-Context with a Single Model

Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents