#Retrieval-Augmented Generation

Articles (7)

• 🇺🇸 Open-Source Reproduction and Explainability Analysis of Corrective Retrieval Augmented Generation — 18/03/2026 [USA]

  arXiv:2603.16169v1 Announce Type: cross Abstract: Corrective Retrieval Augmented Generation (CRAG) improves the robustness of RAG systems by evaluating retrieved document quality and triggering corre...

  Related: #AI Explainability, #Open-Source Research
• 🇺🇸 HubScan: Detecting Hubness Poisoning in Retrieval-Augmented Generation Systems — 27/02/2026 [USA]

  arXiv:2602.22427v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are essential to contemporary AI applications, allowing large language models to obtain external knowled...

  Related: #AI Security, #Cybersecurity Threats, #Vector Database Protection
• 🇺🇸 Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation — 27/02/2026 [USA]

  arXiv:2602.22215v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate potential in the field of scientific idea generation. However, the generated results often lack controllable a...

  Related: #Artificial Intelligence, #Scientific Research, #Knowledge Graphs
• 🇺🇸 Case-Aware LLM-as-a-Judge Evaluation for Enterprise-Scale RAG Systems — 25/02/2026 [USA]

  arXiv:2602.20379v1 Announce Type: cross Abstract: Enterprise Retrieval-Augmented Generation (RAG) assistants operate in multi-turn, case-based workflows such as technical support and IT operations, w...

  Related: #AI Evaluation, #Enterprise Systems
• 🇺🇸 Rethinking Soft Compression in Retrieval-Augmented Generation: A Query-Conditioned Selector Perspective — 19/02/2026 [USA]

  arXiv:2602.15856v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) effectively grounds Large Language Models (LLMs) with external knowledge and is widely applied to Web-related ta...

  Related: #Soft Context Compression, #Scalability Challenges in LLMs, #Auto-Encoder Limitations, #Query-Conditioned Selection
• 🇺🇸 Understand Then Memory: A Cognitive Gist-Driven RAG Framework with Global Semantic Diffusion — 19/02/2026 [USA]

  arXiv:2602.15895v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) effectively mitigates hallucinations in LLMs by incorporating external knowledge. However, the inherent discrete...

  Related: #Artificial intelligence and language modeling, #Human memory analogies in AI, #Hallucination mitigation in generative models, #Semantic integrity in knowledge retrieval
• 🇺🇸 SCAN: Semantic Document Layout Analysis for Textual and Visual Retrieval-Augmented Generation — 16/02/2026 [USA]

  arXiv:2505.14381v3 Announce Type: replace Abstract: With the increasing adoption of Large Language Models (LLMs) and Vision-Language Models (VLMs), rich document analysis technologies for application...

  Related: #AI research, #Document analysis