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Notes on rag
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DUMA-Bench: A Dual-Control Multi-Agent Benchmark for Evaluating LLM Agent Security
DUMA-Bench evaluates agent security when both the agent and user can influence shared environment state. It extends tau-squared bench with adversarial environments covering eight vulnerability classes, including RAG…
AutoViewMem: Self-Configuring Orthogonal Views for Conversational Long-Term Memory
AutoViewMem discovers low-overlap semantic views from interaction traces, uses a compact complementary view set for structured write-time extraction, and grounds memories in provenance. It moves semantic…
RAFT: A Stateful Retrieval-Augmented Framework for Troubleshooting Agents
RAFT models each closed support case as a directed chain of timeline entries and retrieves at the entry level, returning the parent-case trajectory anchored at a matching state. It evaluates against a synthetic…
Q&A on Any Spreadsheet Requires Interpreting Its Grid Structure
The preprint argues that spreadsheet question answering requires interpreting two-dimensional grid structure. It proposes semantic cell-role annotation to improve chunking and interpretability for LLM-driven RAG. The…
TRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives
TRACE is a training-free agentic retrieval framework for historical archives with OCR degradation, heterogeneous document genres, and source-traceability requirements. The preprint describes an internal deployment for…
GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG
The paper introduces GRADRAG, a framework for improving Retrieval-Augmented Generation (RAG) systems by coordinating improvements across different components of the pipeline. It uses feedback from an Evaluator to…
Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization
The paper introduces a framework for comparing different variants of RAG (Rich Automated Generation) scenarios, including GraphRAG and Agentic RAG, in semi-structured knowledge bases. The framework includes nine…
Introducing Mistral OCR 4
Mistral AI released OCR 4, a document intelligence model that extracts text and provides structural metadata: bounding boxes, block classification (titles, tables, equations, signatures), per-page/per-word confidence…
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