Search: “retrieval”

Mesh Memory Protocol: Semantic Infrastructure for Multi-Agent LLM Systems

arXiv:2604.19540v1 Announce Type: cross Abstract: Teams of LLM agents increasingly collaborate on tasks spanning days or weeks: multi-day data-generation sprints where generator, reviewer, and auditor

agentsarxiv-cs-ai

22 Apr 2026

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Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective

DGX agent

arXiv:2505.20816v2 Announce Type: replace Abstract: Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large langua

agentsarxiv-cs-cl

22 Apr 2026

A Survey on the Security of Long-Term Memory in LLM Agents: Toward Mnemonic Sovereignty

arXiv:2604.16548v1 Announce Type: cross Abstract: Research on large language model (LLM) security is shifting from 'will the model leak training data' to a more consequential question: can an agent wi

AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction

arXiv:2510.15339v3 Announce Type: replace Abstract: Building effective knowledge graphs (KGs) for Retrieval-Augmented Generation (RAG) is pivotal for advancing question answering (QA) systems. However

Clinical Note Bloat Reduction for Efficient LLM Use

arXiv:2604.16364v1 Announce Type: cross Abstract: Health systems are rapidly deploying large language models (LLMs) that use clinical notes for clinical decision support applications. However, modern

Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2604.17616v1 Announce Type: new Abstract: Root cause analysis (RCA) for time-series anomaly detection is critical for the reliable operation of complex real-world systems. Existing explanation m

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection

arXiv:2604.17037v1 Announce Type: new Abstract: Deception detection is of great significance for ensuring information security and conducting public opinion analysis, with personality factors and emot

GenericAgent: A Token-Efficient Self-Evolving LLM Agent via Contextual Information Density Maximization (V1.0)

arXiv:2604.17091v1 Announce Type: new Abstract: Long-horizon large language model (LLM) agents are fundamentally limited by context. As interactions become longer, tool descriptions, retrieved memorie

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

model-releasesarxiv-cs-cv

arXiv:2604.18418v1 Announce Type: new Abstract: Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medici

MemBuilder: Reinforcing LLMs for Long-Term Memory Construction via Attributed Dense Rewards

arXiv:2601.05488v3 Announce Type: replace Abstract: Maintaining consistency in long-term dialogues remains a fundamental challenge for LLMs, as standard retrieval mechanisms often fail to capture the

Peerispect: Claim Verification in Scientific Peer Reviews

arXiv:2604.17667v1 Announce Type: new Abstract: Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitt

PPEDCRF: Dynamic-CRF-Guided Selective Perturbation for Background-Based Location Privacy in Video Sequences

model-releasesarxiv-cs-cv

arXiv:2604.17163v1 Announce Type: new Abstract: We propose PPEDCRF, a calibrated selective perturbation framework that protects background-based location privacy in released video frames against galle

Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning

arXiv:2604.16591v1 Announce Type: new Abstract: Large language models (LLMs) sometimes memorize undesirable knowledge, which must be removed after deployment. Prior work on machine unlearning has focu

researcharxiv-cs-lg

Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration

arXiv:2505.21471v2 Announce Type: replace Abstract: With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large q

Sessa: Selective State Space Attention

arXiv:2604.18580v1 Announce Type: cross Abstract: Modern sequence models are dominated by Transformers, where self-attention mixes information from the visible context in an input-dependent way. Howev

StageMem: Lifecycle-Managed Memory for Language Models

arXiv:2604.16774v1 Announce Type: new Abstract: Long-horizon language model systems increasingly rely on persistent memory, yet many current designs still treat memory primarily as a static store: wri

TextTIGER: Text-based Intelligent Generation with Entity Prompt Refinement for Text-to-Image Generation

arXiv:2504.18269v2 Announce Type: replace Abstract: When generating images from prompts that include specific entities, the model must retain as much entity-specific knowledge as possible. However, th

When Misinformation Speaks and Converses: Rethinking Fact-Checking in Audio Platforms

arXiv:2604.16767v1 Announce Type: new Abstract: Audio platforms have evolved beyond entertainment. They have become central to public discourse, from podcasts and radio to WhatsApp voice notes and liv

WorldDB: A Vector Graph-of-Worlds Memory Engine with Ontology-Aware Write-Time Reconciliation

arXiv:2604.18478v1 Announce Type: cross Abstract: Persistent memory is the bottleneck separating stateless chatbots from long-running agentic systems. Retrieval-augmented generation (RAG) over flat ve

'Excuse me, may I say something...' CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations

model-releasesarxiv-cs-ai

arXiv:2604.15588v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into scientific workflows presents exciting opportunities to accelerate biomedical discovery. However,

FACTS: Table Summarization via Offline Template Generation with Agentic Workflows

arXiv:2510.13920v2 Announce Type: replace Abstract: Query-focused table summarization requires generating natural language summaries of tabular data conditioned on a user query, enabling users to acce

Long-Term Memory for VLA-based Agents in Open-World Task Execution

arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical

safetyarxiv-cs-ro

Local Ai

Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization

arXiv:2604.16248v1 Announce Type: new Abstract: Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent

local-aiarxiv-cs-cv

Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation

arXiv:2601.07338v2 Announce Type: replace Abstract: Large Language Models (LLMs) have significantly advanced Machine Translation (MT), applying them to linguistically complex domains-such as Social Ne

Tutorials

Beyond Visual Cues: Semantic-Driven Token Filtering and Expert Routing for Anytime Person ReID

arXiv:2604.15090v1 Announce Type: new Abstract: Any-Time Person Re-identification (AT-ReID) necessitates the robust retrieval of target individuals under arbitrary conditions, encompassing both modali

tutorialsarxiv-cs-cv

CaptionQA: Is Your Caption as Useful as the Image Itself?

model-releasesarxiv-cs-cv

arXiv:2511.21025v2 Announce Type: replace Abstract: Image captions serve as efficient surrogates for visual content in multimodal systems such as retrieval, recommendation, and multi-step agentic infe

Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation

arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a

Caption First, VQA Second: Knowledge Density, Not Task Format, Drives Multimodal Scaling

arXiv:2604.13054v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved rapid progress, yet their scaling behavior remains less clearly characterized and often less pred

16 Apr 2026

RAG or Learning? Understanding the Limits of LLM Adaptation under Continuous Knowledge Drift in the Real World

arXiv:2604.05096v2 Announce Type: replace Abstract: Large language models (LLMs) acquire most of their knowledge during pretraining, which ties them to a fixed snapshot of the world and makes adaptati

16 Apr 2026

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning

arXiv:2505.17086v4 Announce Type: replace Abstract: Large Language Models (LLMs) equipped with modern Retrieval-Augmented Generation (RAG) systems often employ multi-turn interaction pipelines to inte

Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness

arXiv:2604.12811v1 Announce Type: cross Abstract: Dense Associative Memory (DAM) generalizes Hopfield networks through higher-order interactions and achieves storage capacity that scales as O(N^{n-1})

Applications

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To

applicationsarxiv-cs-cl

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

arXiv:2604.12812v1 Announce Type: new Abstract: Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document le

Memory as Metabolism: A Design for Companion Knowledge Systems

model-releasesarxiv-cs-ai

arXiv:2604.12034v1 Announce Type: new Abstract: Retrieval-Augmented Generation remains the dominant pattern for giving LLMs persistent memory, but a visible cluster of personal wiki-style memory archi

M^star: Every Task Deserves Its Own Memory Harness

arXiv:2604.11811v1 Announce Type: cross Abstract: Large language model agents rely on specialized memory systems to accumulate and reuse knowledge during extended interactions. Recent architectures ty

agentsarxiv-cs-ai

MultiDocFusion: Hierarchical and Multimodal Chunking Pipeline for Enhanced RAG on Long Industrial Documents

arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com

Representation geometry shapes task performance in vision-language modeling for CT enterography

arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t

CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation

model-releasesarxiv-cs-ai

arXiv:2604.10504v1 Announce Type: new Abstract: Current large language models (LLMs), even those explicitly trained for reasoning, often struggle with ambiguous content moderation cases due to mislead

CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras

arXiv:2602.18047v3 Announce Type: replace Abstract: City-scale person re-identification across distributed cameras must handle severe appearance changes from viewpoint, occlusion, and domain shift whi

safetyarxiv-cs-cv

Descriptor-Injected Cross-Modal Learning: A Systematic Exploration of Audio-MIDI Alignment via Spectral and Melodic Features

arXiv:2604.10283v1 Announce Type: cross Abstract: Cross-modal retrieval between audio recordings and symbolic music representations (MIDI) remains challenging because continuous waveforms and discrete

safetyarxiv-cs-lg

Local Ai

Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention

arXiv:2512.11811v3 Announce Type: replace-cross Abstract: Crowdsourced social media imagery provides real-time visual evidence of urban flooding but often lacks reliable geographic metadata for emerge

local-aiarxiv-cs-ai

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

arXiv:2502.18026v3 Announce Type: replace-cross Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging t

HTAA: Enhancing LLM Planning via Hybrid Toolset Agentization & Adaptation

arXiv:2604.10917v1 Announce Type: new Abstract: Enabling large language models to scale and reliably use hundreds of tools is critical for real-world applications, yet challenging due to the inefficie

KCS: Diversify Multi-hop Question Generation with Knowledge Composition Sampling

arXiv:2508.20567v2 Announce Type: replace Abstract: Multi-hop question answering faces substantial challenges due to data sparsity, which increases the likelihood of language models learning spurious

Large Language Model as An Operator: An Experience-Driven Solution for Distribution Network Voltage Control

arXiv:2507.14800v2 Announce Type: replace-cross Abstract: With the advanced reasoning, contextual understanding, and information synthesis capabilities of large language models (LLMs), a novel paradig

Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability Calibration

arXiv:2604.10150v1 Announce Type: new Abstract: Generative listwise reranking leverages global context for superior retrieval but is plagued by intrinsic position bias, where models exhibit structural

Legal2LogicICL: Improving Generalization in Transforming Legal Cases to Logical Formulas via Diverse Few-Shot Learning

arXiv:2604.11699v1 Announce Type: cross Abstract: This work aims to improve the generalization of logic-based legal reasoning systems by integrating recent advances in NLP with legal-domain adaptive f

Tutorials

LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape

arXiv:2604.02600v2 Announce Type: replace-cross Abstract: Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This r

tutorialsarxiv-cs-ai