Search: “retrieval”

Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning

arXiv:2601.06943v2 Announce Type: replace-cross Abstract: In real-world video question answering scenarios, videos often provide only localized visual cues, while verifiable answers are distributed ac

19 May 2026

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Research

An LLM-RAG Approach for Healthy Eating Index-Informed Personalized Food Recommendations

DGX agent

arXiv:2605.15213v1 Announce Type: cross Abstract: Diet quality is a leading determinant of chronic disease risk. Advances in artificial intelligence (AI) have enabled food recommendation systems to ad

researcharxiv-cs-ai

18 May 2026

Context Pruning for Coding Agents via Multi-Rubric Latent Reasoning

arXiv:2605.15315v1 Announce Type: new Abstract: LLM-powered coding agents spend the majority of their token budget reading repository files, yet much of the retrieved code is irrelevant to the task at

18 May 2026

Differentially Private Motif-Preserving Multi-modal Hashing

arXiv:2605.15460v1 Announce Type: cross Abstract: Cross-modal hashing enables efficient retrieval by encoding images and text into compact binary codes. State-of-the-art methods rely on semantic simil

18 May 2026

A Heterogeneous Temporal Memory Governance Framework for Long-Term LLM Persona Consistency

arXiv:2605.14802v1 Announce Type: new Abstract: Large language models often suffer from fact loss, timeline confusion, persona drift, and reduced stability during long-range interaction, especially un

DAPL: Integration of Positive and Negative Descriptions in Text-Based Person Search

arXiv:2405.07459v3 Announce Type: replace Abstract: Text-based person search (TBPS) aims to retrieve specific images of individuals from large datasets using textual descriptions. Existing TBPS method

safetyarxiv-cs-cv

FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding

arXiv:2602.03417v2 Announce Type: replace Abstract: Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages

researcharxiv-cs-cl

OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework

arXiv:2603.24422v2 Announce Type: replace-cross Abstract: Generative Retrieval (GR) has emerged as a promising paradigm for modern search systems. Compared to multi-stage cascaded architecture, it off

PolitNuggets: Benchmarking Agentic Discovery of Long-Tail Political Facts

arXiv:2605.14002v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) embedded in agentic frameworks have transformed information retrieval from static, long context question answering into op

SR-Platform: An Agentic Pipeline for Natural Language-Driven Robot Simulation Environment Synthesis

arXiv:2605.14700v1 Announce Type: new Abstract: Generating robot simulation environments remains a major bottleneck in simulation-based robot learning. Constructing a training-ready MuJoCo scene typic

agentsarxiv-cs-ro

Cognifold: Always-On Proactive Memory via Cognitive Folding

arXiv:2605.13438v1 Announce Type: new Abstract: Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cogni

14 May 2026

ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis

model-releasesarxiv-cs-lg

arXiv:2605.12736v1 Announce Type: new Abstract: Template based single step retrosynthesis predicts reactants by selecting and applying an explicit reaction template, making each prediction traceable t

14 May 2026

TimelineReasoner: Advancing Timeline Summarization with Large Reasoning Models

arXiv:2605.12518v1 Announce Type: cross Abstract: The proliferation of online news poses a challenge to extracting structured timelines from unstructured content. While recent studies have shown that

14 May 2026

AOI-SSL: Self-Supervised Framework for Efficient Segmentation of Wire-bonded Semiconductors In Optical Inspection

arXiv:2605.12430v1 Announce Type: new Abstract: Segmentation models in automated optical inspection of wire-bonded semiconductors are typically device-specific and must be re-trained when new devices

researcharxiv-cs-cv

Local Ai

From Image Hashing to Scene Change Detection

arXiv:2605.12259v1 Announce Type: new Abstract: Image hashing provides compact representations for efficient storage and retrieval but is inherently limited to global comparison and cannot reason abou

local-aiarxiv-cs-cv

Generative AI for Visualizing Highway Construction Hazards Through Synthetic Images and Temporal Sequences

arXiv:2605.11276v1 Announce Type: new Abstract: Highway construction workers face a high risk of serious injury or death. Image-based training materials depicting hazardous scenarios are essential for

safetyarxiv-cs-cv

GeoQuery: Geometry-Query Diffusion for Sparse-View Reconstruction

arXiv:2605.12399v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a prominent paradigm for 3D reconstruction and novel view synthesis. However, it remains vulnerable to sever

researcharxiv-cs-cv

Context-Augmented Code Generation: How Product Context Improves AI Coding Agent Decision Compliance by 49%

arXiv:2605.08112v1 Announce Type: cross Abstract: AI coding agents powered by large language models can read codebases and produce functional code, but they routinely violate team-specific product dec

Defense effectiveness across architectural layers: a mechanistic evaluation of persistent memory attacks on stateful LLM agents

arXiv:2605.08442v1 Announce Type: cross Abstract: Persistent memory attacks against LLM agents achieve high attack success rates against open-source models. In these attacks, malicious instructions in

Factual recall in linear associative memories: sharp asymptotics and mechanistic insights

arXiv:2605.10795v1 Announce Type: cross Abstract: Large language models demonstrate remarkable ability in factual recall, yet the fundamental limits of storing and retrieving input--output association

researcharxiv-cs-lg

Human-Inspired Memory Architecture for LLM Agents

arXiv:2605.08538v1 Announce Type: new Abstract: Current LLM agents lack principled mechanisms for managing persistent memory across long interaction horizons. We present a biologically-grounded memory

LegalCiteBench: Evaluating Citation Reliability in Legal Language Models

arXiv:2605.10186v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into legal drafting and research workflows, where incorrect citations or fabricated precedent

MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs

arXiv:2605.10064v1 Announce Type: new Abstract: Self-evolving language-model agents must decide what to learn next and how to preserve what they have learned across iterations. Existing systems typica

Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke

arXiv:2605.09236v1 Announce Type: cross Abstract: While digitized corpora have transformed the study of intellectual transmission, current methods rely heavily on lexical text reuse detection, capturi

MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading

arXiv:2605.10268v1 Announce Type: cross Abstract: To tackle long-context reasoning tasks without the quadratic complexity of standard attention mechanisms, approaches based on agent memory have emerge

Neural at ArchEHR-QA 2026: One Method Fits All: Unified Prompt Optimization for Clinical QA over EHRs

arXiv:2605.10877v1 Announce Type: new Abstract: Automated question answering (QA) over electronic health records (EHRs) demands precise evidence retrieval, faithful answer generation, and explicit gro

safetyarxiv-cs-cl

Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search

model-releasesarxiv-cs-lg

arXiv:2605.08762v1 Announce Type: cross Abstract: Current omni-modal benchmarks mainly evaluate models under settings where multiple modalities are provided simultaneously, while the ability to start

PHMForge: Evaluating LLM Agents on Industrial Prognostics through MCP-Native, Algorithm-Grounded Tools

arXiv:2604.01532v2 Announce Type: replace Abstract: LLM agents are beginning to invoke industrial asset-management tools through the Model Context Protocol (MCP), yet whether they can act reliably on

Qwen Goes Brrr: Off-the-Shelf RAG for Ukrainian Multi-Domain Document Understanding

arXiv:2605.10296v1 Announce Type: cross Abstract: We participated in the Fifth UNLP shared task on multi-domain document understanding, where systems must answer Ukrainian multiple-choice questions fr

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts

arXiv:2605.09033v1 Announce Type: cross Abstract: Graph-based agent memory is increasingly used in LLM agents to support structured long-term recall and multi-hop reasoning, but it also creates a new

TIDE-Bench: Task-Aware and Diagnostic Evaluation of Tool-Integrated Reasoning

arXiv:2605.09544v1 Announce Type: new Abstract: Tool-integrated reasoning has emerged as a promising paradigm for enhancing large language models with external computation, retrieval, and execution ca

TRACER: Verifiable Generative Provenance for Multimodal Tool-Using Agents

arXiv:2605.09934v1 Announce Type: new Abstract: Multimodal large language models increasingly solve vision-centric tasks by calling external tools for visual inspection, OCR, retrieval, calculation, a

Zero-Shot Chinese Character Recognition via Global-Local Dual-Branch Alignment and Hierarchical Inference

model-releasesarxiv-cs-cv

arXiv:2605.08814v1 Announce Type: new Abstract: Chinese character categories are extremely large, and unseen characters frequently arise in open-world scenarios, making zero-shot Chinese character rec

Beyond Factual Accuracy: Evaluating Global Reasoning Integrity in RAG Systems with LogicScore

arXiv:2601.15050v4 Announce Type: replace Abstract: Current evaluation methods for Retrieval Augmented Generation (RAG) suffer from extit{factual myopia}: they relentlessly emphasize factual accuracy

Applications

From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle

arXiv:2605.06963v1 Announce Type: cross Abstract: This demo paper describes the development of the AI Teaching & Learning Assistant, a modular Moodle plugin that leverages Retrieval-Augmented Generati

applicationsarxiv-cs-ai

MemCompiler: Compile, Don't Inject -- State-Conditioned Memory for Embodied Agents

arXiv:2605.07594v1 Announce Type: new Abstract: Existing memory systems for embodied agents typically inject retrieved memory as static context at episode start, a paradigm we term Ahead-of-time Monol

agentsarxiv-cs-ro

MIPIAD: Multilingual Indirect Prompt Injection Attack Defense with Qwen -- TF-IDF Hybrid and Meta-Ensemble Learning

arXiv:2605.07269v1 Announce Type: new Abstract: Indirect prompt injection remains a persistent weakness in retrieval-augmented and tool-using LLM systems, and the problem becomes harder to characteris

Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding

arXiv:2605.07575v1 Announce Type: cross Abstract: Proactive streaming video understanding requires Video-LLMs to decide when to respond as a video unfolds, a task where existing methods often fall sho

Local Ai

Self Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale

arXiv:2605.07022v1 Announce Type: new Abstract: Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are expensive to maintain, lag behind primary literature, a

local-aiarxiv-cs-lg

TajPersLexon: A Tajik-Persian Lexical Resource and Hybrid Model for Cross-Script Low-Resource NLP

arXiv:2605.06886v1 Announce Type: new Abstract: This work introduces TajPersLexon, a curated Tajik--Persian parallel lexical resource of 40,112 word and short-phrase pairs for cross-script lexical ret

TRACE: Tourism Recommendation with Accountable Citation Evidence

arXiv:2605.07677v1 Announce Type: cross Abstract: Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once

When Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent Memory

arXiv:2605.07313v1 Announce Type: new Abstract: Memory-agent evaluations report fixed-snapshot accuracy or retrieval quality, but these scores do not show whether evidence remains usable as irrelevant

DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation

arXiv:2605.04458v1 Announce Type: new Abstract: Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generat

researcharxiv-cs-cl

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

arXiv:2605.03205v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowled

UniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings

arXiv:2505.11815v2 Announce Type: replace Abstract: Current vision-language models have been explored for multi-modal embedding tasks like information retrieval. However, they face significant challen

safetyarxiv-cs-cv

What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

arXiv:2605.03354v1 Announce Type: new Abstract: Agent memory failures are silent: an LLM-based agent can produce a fluent response even when it fails to extract, retain, or retrieve the information ne

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

6 May 2026

AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelines

arXiv:2605.02967v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances LLMs, but performance is highly sensitive to complex architecture designs and hyper-parameter configurat