Retrieval and RAG
29 notes, newest first. Includes the vault tags information retrieval, retrieval-augmented generation, rag, knowledge graphs.
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…
Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models
The study introduces a framework to automate the construction of Dynamic Master Logic (DML) models for complex systems using Retrieval-Augmented Generation and Large Language Models. These models, represented as…
Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence
The study introduces Mechanist, an AI system designed to autonomously discover the mechanisms behind AI intelligence. It uses a knowledge graph of approximately 13,000 papers integrated with a multidisciplinary…
KGCaRe: Explainable Complex Conditional Question Answering using Automatic Knowledge Graph Construction and Context Retrieval with LLMs
The study proposes a new method called KGCaRe for answering complex conditional questions using large language models (LLMs) and retrieval-augmented generation (RAG). This approach combines neural retrieval with…
Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations
A research paper proposes a new method for document search called Reliable Embedding-free Agentic Document-search (READ), which is designed to overcome limitations in current methods for long documents, particularly…
Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations
The paper introduces a new approach called READ (Reliable Embedding-free Agentic Document-search) for retrieving information from long documents such as financial statements and audit reports. The traditional method of…
Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations
The paper proposes a new approach for document search called 'READ (Reliable Embedding-free Agentic Document-search)', which aims to address the issues with current black-box retrieval designs in handling long…
Comparative Approaches to Agent Retrieval over Large Skill Libraries
The study compares two systems for deciding which skills to load from large skill libraries in AI agents. The first system is a hybrid ranker that combines lexical and dense-embedding retrieval for sparse, on-demand…
Comparative Approaches to Agent Retrieval over Large Skill Libraries
Researchers compared two methods for deciding which skills to load from large skill libraries in AI agents: a hybrid ranker combining lexical and dense-embedding retrieval, and a typed knowledge graph encoding workflow…
AskChem: Claim-Centered Infrastructure for Chemistry Literature Synthesis
AskChem is a system designed to help scientists and AI agents find specific information in chemistry literature more efficiently. It changes the unit of retrieval from entire papers to 'claims', which are atomic, typed…
A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility
Researchers introduce APS-RAG, a platform that makes it easier for staff at the Advanced Photon Source (APS) to access institutional knowledge through natural language queries. The platform combines multiple channels…
A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility
Researchers have developed a platform called APS-RAG for scientific facilities like the Advanced Photon Source (APS). The platform aims to make the vast amount of institutional knowledge accessible through natural…
GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG
The authors present GRADRAG, a framework for improving Retrieval-Augmented Generation (RAG) systems by coordinating updates across multiple agents in the pipeline. The system uses feedback from an Evaluator to update…
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…
GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG
The paper introduces GRADRAG, a framework that improves Retrieval-Augmented Generation (RAG) systems by coordinating improvements across the pipeline. Instead of optimizing components in isolation, GRADRAG models the…
PLAID-PRF: Pseudo-Relevance Feedback with Centroid-like Tokens in PLAID
Researchers propose a method called PLAID-PRF to improve the effectiveness of multi-vector dense retrieval models like ColBERT. This method uses centroid-based quantization in PLAID, a model that reduces index size and…
Reachability-Aware Pretraining for Efficient Target-Oriented Path Exploration in Temporal Knowledge Graph Reasoning
The authors propose a new method called RAPTOR for improving the efficiency of target-oriented path exploration in temporal knowledge graphs (TKG). The method injects a reachability-aware inductive bias to the agent…
SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration
Researchers introduce SearchOS, a system-level framework designed to improve the efficiency of multi-agent information-seeking systems. By making search progress explicit and persistent, it helps prevent repetitive…
SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration
The paper introduces SearchOS, a system-level multi-agent framework designed to improve the quality and completeness of search results in open-domain information-seeking tasks. The framework addresses the issue of…
Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education
The paper introduces Earthquaker-AI, a hybrid educational framework that uses Lego WeDo2 robotics for earthquake simulations and an AI assistant for guided learning and feedback. The system aims to enhance earthquake…
TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting
The paper introduces TopoBrick, a framework for zero-shot forecasting of Internet-of-Things (IoT) data in buildings, which does not require training and takes into account the physical topology, spatial hierarchy, and…
Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval
Researchers propose a method to improve the quality of data retrieval from structured metadata catalogs by introducing permutation-invariant fine-tuning (PI-FT). This technique helps in maintaining the same retrieval…
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…
Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization
The authors present a framework for evaluating and comparing different types of RAG (Retrieval Augmented Generation) scenarios, including GraphRAG and Agentic RAG. They provide implementations for nine standardized RAG…
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…
