Search: “retrieval”

arXiv:2610.12666v1 Announce Type: cross Abstract: We introduce iRAG, a human-in-the-loop decision-support system combining Retrieval-Augmented Generation (RAG) with Hybrid Decision-Making. Unlike conv

agentsarxiv-cs-ai

12 Oct 2026

Human

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RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees

DGX agent

arXiv:2610.11370v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) grounds language models in external corpora. Agentic RAG enables iterative search, yet exposes the model to isolate

model-releasesarxiv-cs-ai

9 Oct 2026

Memory Depth and Reconstructed Context Width: A Controlled Evaluation of Hierarchical Retrieval

arXiv:2610.08300v1 Announce Type: new Abstract: Long-term conversational memory is becoming an integral component of modern LLM systems. Proposed architectures group records by topics and events, cons

applicationsarxiv-cs-cl

7 Oct 2026

NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI

arXiv:2610.06502v1 Announce Type: new Abstract: Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, an

researcharxiv-cs-cv

6 Oct 2026

Hardware

PARK: Accurate Block Retrieval for Sparse Attention in Video Diffusion Transformers

arXiv:2609.38978v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a dominant architecture for video generation, but their efficiency is limited by the quadratic complexity of f

hardwarearxiv-cs-cv

1 Oct 2026

Agents

TAGGRAPH: Tag-Augmented Graphs for Graph Retrieval of Agent Persistent Histories

arXiv:2609.38353v1 Announce Type: cross Abstract: Long-term memory lets LLM agents recall past interactions and remain consistent across sessions, but memory systems are hard to compare because they o

agentsarxiv-cs-ai

1 Oct 2026

Effective Dense Retrieval using Only In-Context Examples

arXiv:2609.38099v1 Announce Type: cross Abstract: Turning decoder-only large language models (LLMs) into strong dense retrievers typically requires some form of retriever training. In this paper, we a

30 Sept 2026

Geometry-Conditioned Fixed-Scaffold Encoders for Time-Warp Robust Sequence Retrieval

arXiv:2609.36809v1 Announce Type: new Abstract: Embedding-based retrieval is attractive for long sequence collections because each item can be encoded once and searched by nearest-neighbor ranking. Th

30 Sept 2026

Beyond Retrieval Relevance: Scene-Grounded Risk Entailment for Vision-Language Driving

arXiv:2609.34145v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) gives vision--language driving systems access to external safety knowledge, yet a retrieved risk rule may be releva

safetyarxiv-cs-ro

29 Sept 2026

Cross-Lingual Legal QA for Vietnamese Labour Law: Retrieval, Translation, and Verifier-Guided Correction

arXiv:2609.27376v1 Announce Type: new Abstract: Cross-lingual legal question answering must retrieve statutes across languages while preventing unsupported legal claims. We introduce a bilingual evalu

applicationsarxiv-cs-cl

24 Sept 2026

ChemCLIR-Bench: Benchmarking Cross-Lingual Information Retrieval in Multilingual Chemical Patents

arXiv:2609.23231v1 Announce Type: new Abstract: Cross-lingual information retrieval (CLIR) is increasingly important in multi-national industries, where critical technical evidence may exist in a diff

22 Sept 2026

Crash Narrative-Guided Countermeasure Recommendation Using Large Language Models: A Retrieval-Augmented Generation Framework for Intersection Safety

arXiv:2609.15997v1 Announce Type: new Abstract: Improving safety at intersections requires identifying crash mechanisms and recommending appropriate countermeasures. However, this process traditionall

safetyarxiv-cs-cl

16 Sept 2026

Local Ai

Retrieval-Driven Memory Reconsolidation for Long-Term LLM Agents

arXiv:2609.16053v1 Announce Type: cross Abstract: Long-term memory is essential for LLM-based agents operating over extended interactions. Existing memory systems primarily update memory when new info

local-aiarxiv-cs-ai

16 Sept 2026

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

15 Sept 2026

Hypergraph-Regularized Gramian Volumes for Multimodal Retrieval

arXiv:2609.15320v1 Announce Type: new Abstract: Volume-based multimodal retrieval jointly scores a text query with a candidate's video, audio, and subtitle embeddings. While this approach captures hig

safetyarxiv-cs-cv

15 Sept 2026

Option-Aware Retrieval and Task-Specific VLM Adaptation for Medical VQA

arXiv:2609.15530v1 Announce Type: new Abstract: We describe our submission to the MedReason 2026 challenge, covering multiple-choice (MCQ) and open-ended (OE) medical visual question answering (VQA) u

15 Sept 2026

R2VC: Modular Fact-Checking with Retrieval, Verification, and Confidence Calibration

arXiv:2609.11955v1 Announce Type: new Abstract: Large language models are increasingly used for automated fact checking, but end-to-end prompting often entangles evidence retrieval, reasoning, and unc

14 Sept 2026

RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM Safety

arXiv:2609.11758v1 Announce Type: new Abstract: Allowing large language models (LLMs) to retrieve information from a set of trusted documents can increase reliability and reduce hallucination. However

11 Sept 2026

A Hierarchical Consistency Framework for Auditing Retrieval-Augmented Generation Systems

arXiv:2609.07075v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is commonly evaluated by whether the final answer is correct. That test is insufficient: an answer can match its re

AAS-RAIL: Improving Information Extraction for Asset Administration Shells through Retrieval-Augmented In-Context Learning

arXiv:2609.07334v1 Announce Type: new Abstract: The Asset Administration Shell (AAS) is a cornerstone of Industry 4.0 and the Digital Product Passport, providing standardized digital representations o

CARRE: Counterfactual Action Retrieval and Reason Evaluation for Explainable Churn Prescription

arXiv:2609.09766v1 Announce Type: new Abstract: Churn models typically identify high-risk customers but do not specify which feasible retention action should be considered or why that action is approp

PACE: Perceived-Latency-Aware Cascading Service Routing and Filler Control for QoE-Efficient Retrieval-Augmented Dialogue Serving

arXiv:2609.10372v1 Announce Type: new Abstract: We present the PACE, a framework for retrieval-augmented dialogue serving that formalizes Perceived Time-to-First-Response (PTFR) as a QoE objective and

researcharxiv-cs-cv

Intrinsic Temporal Adaptation of CLIP for Partially Relevant Video Retrieval

model-releasesarxiv-cs-cv

arXiv:2609.04800v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos that contain moments relevant to a text query. Since the target moment occup

7 Sept 2026

Molecular Deja Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

arXiv:2609.05381v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on molecular property benchmarks, but accuracy cannot distinguish a model that predicts a proper

7 Sept 2026

Shadow Queries for Private Retrieval in Vector Databases

arXiv:2609.04767v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on information retrieval (IR) systems, such as Retrieval-Augmented Generation (RAG), to incorporate domai

7 Sept 2026

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

arXiv:2609.01601v1 Announce Type: cross Abstract: The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repos

applicationsarxiv-cs-ai

2 Sept 2026

Automated Tree Knowledge Graph Construction using Ontology Expansion and Retrieval from Vietnamese History Textbooks

arXiv:2609.00763v1 Announce Type: new Abstract: Hierarchical Knowledge graph (KG)-based retrieval augmented generation (RAG) has emerged as a powerful approach for supporting large language models wit

2 Sept 2026

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

2 Sept 2026

AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing

arXiv:2608.29622v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs), yet existing RAG systems often struggle with complex, mu

Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs

arXiv:2502.10673v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has become an effective method for enhancing large language models (LLMs) with up-to-date knowledge. Howe

Evaluating Perspectival Biases in Cross-Modal Retrieval

arXiv:2510.26861v4 Announce Type: replace-cross Abstract: Multimodal retrieval systems are expected to operate in a semantic space, agnostic to the language or cultural origin of the query. In practic

From Location Phrases to Geographic Entities: Task-Adapted Retrieval for People Search

arXiv:2608.28965v1 Announce Type: new Abstract: People search must map free-form location phrases to geographic entities used as structured retrieval filters. Lexical standardizers handle canonical na

Preference Shapes Relevance: Cross-component Hierarchical Semantic Alignment for Personalized Generative Retrieval

arXiv:2608.30553v1 Announce Type: cross Abstract: Generative Retrieval (GR) has emerged as a promising paradigm by mapping queries directly to Semantic IDs (SIDs) with powerful representation capabili

Retrieval-Augmented LLM Agents: Learning to Learn from Experience

arXiv:2603.18272v2 Announce Type: replace Abstract: While large language models (LLMs) have advanced the development of general-purpose agents, robust generalization to unseen tasks remains challengin

PailitaoGR: Latent Think-with-Images for Generative Image Retrieval

arXiv:2608.26658v1 Announce Type: cross Abstract: Generative retrieval has demonstrated strong performance by directly generating product semantic identifiers (SIDs). Extending this paradigm to image

28 Aug 2026

SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval

arXiv:2606.18801v2 Announce Type: replace-cross Abstract: With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for g

28 Aug 2026

CaSKG: Counterfactual-Causal Skill Graphs for Scalable Agent Skill Retrieval

arXiv:2608.25500v1 Announce Type: cross Abstract: Reusable skill libraries allow large language model (LLM) agents to reuse procedural knowledge across tasks, but they also turn memory access into a c

27 Aug 2026

Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models

arXiv:2608.24042v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performan

26 Aug 2026

Reading Is Not Using: Retrieval, Judgment, and the Design of AI Financial Research Workflows

arXiv:2608.24842v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as AI analysts to process financial disclosures and support AI-assisted investment decisions. Y

26 Aug 2026

Wontopos Tablet 2: Measuring Multilingual and Multimodal Memory Retrieval Without Lexical Matching

arXiv:2608.23920v1 Announce Type: cross Abstract: We measure tablet-2, a production long-term memory engine for language models, on the text benchmarks the field already uses and on cross-lingual retr

applicationsarxiv-cs-cv

26 Aug 2026

Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice Prediction

arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models

GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoning

arXiv:2608.22479v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enables LLMs to access external knowledge for answering knowledge-intensive questions. For complex multi-hop questi

safetyarxiv-cs-cl

SCAR: Semantic Continuity-Aware Retrieval for Efficient Context Expansion in RAG

arXiv:2606.16661v2 Announce Type: replace-cross Abstract: Fixed-length chunking in Retrieval-Augmented Generation (RAG) often leads to boundary fragmentation, where critical evidence is split across s

safetyarxiv-cs-cl

W-RAG: Source-Aware Retrieval for Enterprise Document Generation from Heterogeneous Knowledge Bases

arXiv:2608.22081v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to incorporate external knowledge during generation, improving factual grounding an

applicationsarxiv-cs-cl

Representation Affects Retrieval: A Case Study of Skill Discovery and Routing in a Multimodal Agent Harness

arXiv:2608.20389v1 Announce Type: new Abstract: A production agent harness must discover and rank, from a growing library of skills, the one most appropriate for a user's task. At small scale this sel

24 Aug 2026

SKILL-RAG: Self-Knowledge Induced Learning and Filtering for Retrieval-Augmented Generation

arXiv:2509.20377v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has significantly improved the performance of large language models (LLMs) on knowledge-intensive tasks i

24 Aug 2026

CABLE: Extending the Reach of Memory Retrieval via Complementary Antecedent-Based Linking and Expansion

arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev

19 Aug 2026

DEPT: Document Embedding Preservation Tuning for Unified Query Expansion and Retrieval

arXiv:2608.17632v1 Announce Type: cross Abstract: Large language models (LLMs) can both expand underspecified queries and encode text as dense representations, suggesting a unified model for query exp