Search: “retrieval”

Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents

arXiv:2606.30306v1 Announce Type: cross Abstract: Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions. We treat them as persistent-state

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Analytic Concept-Centric Memory for Agentic Embodied Manipulation

DGX agent

arXiv:2606.29774v1 Announce Type: new Abstract: Long-horizon embodied manipulation requires agents to remember persistent objects, track changing scene states, and reuse prior interaction knowledge. H

safetyarxiv-cs-ro

30 Jun 2026

Carolina Guide: A Multi-Agent RAG System with Institutional Guardrails for Academic Policy Assistance

arXiv:2606.28360v1 Announce Type: cross Abstract: University students often struggle to navigate complex academic policies, leading to advising bottlenecks and delayed access to critical information.

safetyarxiv-cs-ai

CLIMP: Contrastive Language-Image Mamba Pretraining

arXiv:2601.06891v2 Announce Type: replace Abstract: Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and

researcharxiv-cs-cv

Tutorials

Contrastive vision-language learning with paraphrasing and negation

arXiv:2511.16527v2 Announce Type: replace Abstract: Contrastive vision-language models continue to be the dominant approach for image-text retrieval. Contrastive Language-Image Pre-training (CLIP) tra

tutorialsarxiv-cs-cv

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a

Tutorials

Grounding LLM Reasoning under Incomplete Graph Evidence

arXiv:2606.30247v1 Announce Type: new Abstract: Knowledge graphs can guide large language models (LLMs) reasoning, but the graph seen by a system is usually a retrieved, linked, temporally scoped, and

tutorialsarxiv-cs-cl

Making Multimodal LLMs Reliable Chart Data Extractors: A Benchmark and Training Framework

arXiv:2606.29808v1 Announce Type: cross Abstract: Chart data extraction, which reverse-engineers data tables from chart images, is essential for reproducibility, analysis, retrieval, and redesign. Exi

Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces

model-releasesarxiv-cs-lg

arXiv:2606.27917v1 Announce Type: new Abstract: Contextual bandits with graph-structured arms arise in recommendation, citation retrieval, and social advertising, where arms connected on a graph tend

29 Jun 2026

When Multi-Robot Systems Meet Agentic AI:Towards Embodied Collective Intelligence

arXiv:2606.27929v1 Announce Type: new Abstract: Embodied AI is increasingly becoming agentic, shifting robots from perception--control pipelines towards closed-loop systems that can retrieve context,

agentsarxiv-cs-ro

29 Jun 2026

Hybrid privacy-aware semantic search: SVD-truncated document geometry and CKKS-encrypted query reranking under a restricted threat model

arXiv:2606.26373v1 Announce Type: cross Abstract: Dense embeddings power semantic search and retrieval-augmented generation, but embedding-inversion attacks can reconstruct source text from a vector:

26 Jun 2026

Scoring Is Not Enough: Addressing Gaps in Utility-fairness Trade-offs for Ranking

arXiv:2606.26369v1 Announce Type: cross Abstract: Scoring functions are used to represent the relevance of individual documents. In modern information retrieval or recommendation systems, they are oft

safetyarxiv-cs-lg

26 Jun 2026

BitNet Text Embeddings

arXiv:2606.25674v1 Announce Type: new Abstract: LLM-based text embedders have substantially improved retrieval and semantic representation quality, but their deployment remains costly: large backbone

researcharxiv-cs-cl

Applications

Edges Before Embeddings: A Confidence-Aware Blur Gate for Vision-Language Pipelines

arXiv:2606.25838v1 Announce Type: new Abstract: Production vision pipelines silently degrade on blurry input, wasting compute on downstream OCR, retrieval, and vision-language model (VLM) calls that c

applicationsarxiv-cs-cv

Local Ai

Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory

arXiv:2606.25115v1 Announce Type: new Abstract: On-device language-model agents improve by accumulating experience in retrieved memory rather than by updating weights. This memory is hard-bounded and

local-aiarxiv-cs-lg

GRAFT: Graph-Based Affordance Transfer via Part Correspondence

arXiv:2606.25241v1 Announce Type: new Abstract: Generalizing robotic manipulation to unseen objects remains challenging, as learning-based approaches require many demonstrations and fail in few-shot s

researcharxiv-cs-ro

Holographic Memory for Zero-Shot Compositional Reasoning in Knowledge Graphs: A Mechanistic Study of Where and Why It Fails

arXiv:2606.24948v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) models predict single-hop links well but have no mechanism for zero-shot compositional queries: multi-hop questions whos

researcharxiv-cs-lg

How Large Language Models Source Brand Reputation Across Languages and Markets

arXiv:2606.25787v1 Announce Type: cross Abstract: When a large language model (LLM) answers a question about a company, it grounds the answer in retrieved web sources, and those sources decide what th

researcharxiv-cs-cl

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG

arXiv:2606.25191v1 Announce Type: cross Abstract: Multi-agent document assessment for retrieval-augmented generation is computationally expensive, driving practitioners toward smaller, deployable mode

agentsarxiv-cs-cl

Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines

arXiv:2601.23132v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-

From Open Waters to Enclosed Cabins: ProteusVPR for Cross-Scene Visual Place Recognition in Maritime Perception and Cabin Inspection

arXiv:2606.24234v1 Announce Type: new Abstract: Autonomous robotic inspection in maritime environments presents unique challenges for Visual Place Recognition (VPR) due to cross-scene perceptual shift

agentsarxiv-cs-cv

I’m headed to San Francisco for AI Engineer World's Fair next week. Two things. I'm giving a talk Tuesday, June 30: 'The unreasonable effect…

I’m headed to San Francisco for AI Engineer World's Fair next week. Two things. I'm giving a talk Tuesday, June 30: 'The unreasonable effectiveness of BM25 for agentic search.' GPT-5 is shockingly goo

model-releasesswyx--x

Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission

model-releasesarxiv-cs-lg

arXiv:2606.23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the up

Quantifying Prior Dominance in RAG Systems

arXiv:2606.23695v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Models in external knowledge, yet current evaluations rely on discrete heuristics that suf

Towards Version-aware Operations and Transaction Memories for Multi-layer MeMo

arXiv:2606.24040v1 Announce Type: cross Abstract: MeMo proposes language models with explicit multi-layer correlation matrix memories (CMMs), where memorization, retrieval, and forgetting are architec

Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space

model-releasesarxiv-cs-lg

arXiv:2606.21109v1 Announce Type: new Abstract: Virtual-cell and perturbation models are increasingly used to predict cellular responses for biomedical discovery, but chemical and genetic perturbation

CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora

model-releasesarxiv-cs-cv

arXiv:2606.20608v1 Announce Type: cross Abstract: Generative text-to-video systems can produce visually fluent educational clips, but they rarely encode the pedagogical content knowledge (PCK) needed

Hardware

Fast-TurboQuant: A Multiplier-Free Online Vector Quantization Approach

arXiv:2606.21448v1 Announce Type: new Abstract: As large language models scale, memory bandwidth for key-value caches and retrieval-augmented generation systems becomes a critical bottleneck. While 1-

hardwarearxiv-cs-lg

Hardware

FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism

arXiv:2606.22180v1 Announce Type: cross Abstract: Graph embedding maps graph nodes into low-dimensional vectors to support applications such as recommendation, fraud detection, and graph-based retriev

hardwarearxiv-cs-lg

Tutorials

NGPS: Structure-Preserving Self-Supervised Denoising via Neighbor-Guided Patch Sampling

arXiv:2606.23200v1 Announce Type: cross Abstract: Neighboring-slice self-supervised denoising is attractive for volumetric medical imaging, yet inter-slice misalignment breaks anatomical correspondenc

tutorialsarxiv-cs-cv

Pre-Generation Hallucination Detection in Large Language Models via Soft-Target Attention Probing

arXiv:2606.21917v1 Announce Type: cross Abstract: Detecting hallucination risk before generation enables abstention, retrieval augmentation, and routing decisions without incurring the cost of decodin

researcharxiv-cs-lg

Hardware

Real-time pedestrian attribute recognition with YOLOv8 and ResNet18

arXiv:2606.21200v1 Announce Type: new Abstract: Pedestrian attribute recognition (PAR) assigns semantic labels to detected pedestrians and is useful in surveillance, video retrieval, and human-centere

hardwarearxiv-cs-cv

Your data changes and your multi-hop RAG goes stale? This one updates with embed-and-append -> open-weights Llama-3.3-70B, your own vLLM endpoint, no graph rebuild

This post discusses a solution for keeping multi-hop retrieval-augmented generation (RAG) systems updated when data changes, using an embed-and-append approach with the open-weights Llama-3.3-70B mode

model-releasesr-ollama

21 Jun 2026

A PubMed-Scale Dataset of Structured Biomedical Abstracts

model-releasesarxiv-cs-cl

arXiv:2606.11361v1 Announce Type: cross Abstract: Structured abstracts are important for biomedical literature processing, by facilitating information retrieval, text mining, and knowledge synthesis.

Can AI Agents Synthesize Scientific Conclusions?

arXiv:2606.11337v1 Announce Type: new Abstract: Scientific AI agents increasingly retrieve evidence, reason across sources, and synthesize conclusions used in consequential decisions. Yet, their abili

External Experience Serving in Production LLM Systems: A Deployment-Oriented Study of Quality-Cost Trade-offs

arXiv:2606.11806v1 Announce Type: new Abstract: Production LLM systems accumulate reusable operational experience, but the practical deployment issue is not merely whether such experience can help. It

safetyarxiv-cs-cl

Fanar-Sadiq: A Multi-Agent Architecture for Grounded Islamic QA

arXiv:2603.08501v3 Announce Type: replace Abstract: Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especial

agentsarxiv-cs-cl

MedCTA: A Benchmark for Clinical Tool Agents

arXiv:2606.11702v1 Announce Type: cross Abstract: To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acqui

MLT-Dedup: Efficient Large-Scale Online Video Deduplication via Multi-Level Representations and Spatial-Temporal Matching

arXiv:2606.12215v1 Announce Type: new Abstract: The explosive growth of user-generated video content on online platforms is accompanied by the emergence of numerous near-duplicate videos--videos that

safetyarxiv-cs-cv

Natural-Language Temporal Grounding in Hour-Long Videos is a Search Problem: A Benchmark and Empirical Decomposition

arXiv:2606.12300v1 Announce Type: cross Abstract: Temporal grounding--returning the interval [t_s, t_e] for a natural-language query over a video--is the language interface to long-form video, yet has

Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines

arXiv:2501.00745v3 Announce Type: replace-cross Abstract: The increasing integration of Large Language Model (LLM) based search engines has transformed the landscape of information retrieval. However,

10 Jun 2026

From Context-Aware to Conflict-Aware: Generalizing Contrastive Decoding for Knowledge Conflict in LLMs

arXiv:2606.10298v1 Announce Type: new Abstract: When large language models generate from retrieved or augmented contexts, conflicts between external context and parametric priors remain a central reli

10 Jun 2026

Is Task-Specific Training Necessary for Anomaly Detection?

arXiv:2601.22763v3 Announce Type: replace Abstract: Current state-of-the-art multi-class unsupervised anomaly detection (MUAD) methods rely on training encoder--decoder models to reconstruct anomaly-f

researcharxiv-cs-cv

10 Jun 2026

Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models

arXiv:2606.08571v1 Announce Type: cross Abstract: Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to quest

CRANE: Knowledge Editing for Reasoning MLLMs

model-releasesarxiv-cs-cv

arXiv:2606.09033v1 Announce Type: new Abstract: The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers,

Industry

Drone boat picked up downed US Army helicopter pilots—a first for sea rescues

A US military autonomous surface vessel marked the first publicized use of an unmanned drone boat to locate and retrieve downed aircrew in real-world warfare. The unmanned vessel helped rescue two Arm

industryars-technica

Extending Ontologies: From Dense Embeddings to Hybrid Quantum-Fuzzy Systems

arXiv:2606.08658v1 Announce Type: new Abstract: LLMs have revolutionized knowledge representation and retrieval, but lack the explicit modeling that knowledge ontologies possess. This paper surveys th

From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG

arXiv:2603.03292v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit high reasoning capacity in medical question-answering, but their tendency to produce hallucinations and o

agentsarxiv-cs-ai