Search: “rag”

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

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GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

DGX agent

arXiv:2604.12285v1 Announce Type: new Abstract: To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining

agentsarxiv-cs-ai

15 Apr 2026

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

Local-Splitter: A Measurement Study of Seven Tactics for Reducing Cloud LLM Token Usage on Coding-Agent Workloads

arXiv:2604.12301v1 Announce Type: cross Abstract: We present a systematic measurement study of seven tactics for reducing cloud LLM token usage when a small local model can act as a triage layer in fr

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

OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation

arXiv:2604.12872v1 Announce Type: new Abstract: Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen environment, which is an ability often required in the accomp

agentsarxiv-cs-ro

When to Forget: A Memory Governance Primitive

arXiv:2604.12007v1 Announce Type: new Abstract: Agent memory systems accumulate experience but currently lack a principled operational metric for memory quality governance -- deciding which memories t

Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models

arXiv:2604.10697v1 Announce Type: new Abstract: Large language models frequently exhibit hallucinations: fluent and confident outputs that are factually incorrect or unsupported by the input context.

Beyond Fluency: Toward Reliable Trajectories in Agentic IR

arXiv:2604.04269v2 Announce Type: replace Abstract: Information Retrieval is shifting from passive document ranking toward autonomous agentic workflows that operate in multi-step Reason-Act-Observe lo

BLUEmed: Retrieval-Augmented Multi-Agent Debate for Clinical Error Detection

arXiv:2604.10389v1 Announce Type: new Abstract: Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a pe

CodeComp: Structural KV Cache Compression for Agentic Coding

arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value

local-aiarxiv-cs-cl

Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping Software

arXiv:2604.10875v1 Announce Type: cross Abstract: AI governance efforts increasingly rely on audit standards: agreed-upon practices for conducting audits. However, poorly designed standards can hide a

Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation

arXiv:2604.10741v1 Announce Type: cross Abstract: Recent agentic search frameworks enable deep research via iterative planning and retrieval, reducing hallucinations and enhancing factual grounding. H

Diagnosing Retrieval vs. Utilization Bottlenecks in LLM Agent Memory

arXiv:2603.02473v2 Announce Type: replace Abstract: Memory-augmented LLM agents store and retrieve information from prior interactions, yet the relative importance of how memories are written versus h

ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios

arXiv:2604.09603v1 Announce Type: cross Abstract: Speculative Decoding promises to accelerate the inference of Large Language Models, yet its efficacy often degrades in production-grade serving. Exist

EDUMATH: Generating Standards-aligned Educational Math Word Problems

arXiv:2510.06965v2 Announce Type: replace-cross Abstract: Math word problems (MWPs) are critical K-12 educational tools, and customizing them to students' interests and ability levels can enhance lear

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

Tutorials

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning

arXiv:2604.10455v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled promising progress in diagnosis prediction from electronic health records (EHRs). However,

tutorialsarxiv-cs-cl

Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method

arXiv:2604.11209v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of applications especially when augmented by external knowledge thro

HiEdit: Lifelong Model Editing with Hierarchical Reinforcement Learning

arXiv:2604.11214v1 Announce Type: new Abstract: Lifelong model editing (LME) aims to sequentially rectify outdated or inaccurate knowledge in deployed LLMs while minimizing side effects on unrelated i

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

LaMI: Augmenting Large Language Models via Late Multi-Image Fusion

arXiv:2406.13621v2 Announce Type: replace Abstract: Commonsense reasoning often requires both textual and visual knowledge, yet Large Language Models (LLMs) trained solely on text lack visual groundin

LLMs for Text-Based Exploration and Navigation Under Partial Observability

arXiv:2604.09604v1 Announce Type: new Abstract: Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language m

MARLIN: Multi-Agent Reinforcement Learning Guided by Language-Based Inter-Robot Negotiation

arXiv:2410.14383v4 Announce Type: replace Abstract: Multi-agent reinforcement learning is a key method for training multi-robot systems. Through rewarding or punishing robots over a series of episodes

safetyarxiv-cs-ro

MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval

arXiv:2604.09552v1 Announce Type: cross Abstract: Engineering rulebooks and technical standards contain multimodal information like dense text, tables, and illustrations that are challenging for retri

PatchRecall: Patch-Driven Retrieval for Automated Program Repair

arXiv:2604.10481v1 Announce Type: cross Abstract: Retrieving the correct set of files from a large codebase is a crucial step in Automated Program Repair (APR). High recall is necessary to ensure that

Scaling unstructured enterprise knowledge with BigQuery Graph, and Kineviz GraphXR

model-releasesgoogle-cloud-ai

Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to a

SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation

arXiv:2604.09551v1 Announce Type: cross Abstract: Cross-domain recommendation (CDR) addresses the data sparsity and cold-start problems in the target domain by leveraging knowledge from data-rich sour

WisPaper: Your AI Scholar Search Engine

arXiv:2512.06879v3 Announce Type: replace-cross Abstract: We present extsc{WisPaper}, an end-to-end agent system that transforms how researchers discover, organize, and track academic literature. The

Beyond Relevance: Utility-Centric Retrieval in the LLM Era

arXiv:2604.08920v1 Announce Type: cross Abstract: Information retrieval systems have traditionally optimized for topical relevance-the degree to which retrieved documents match a query. However, relev

Case-Grounded Evidence Verification: A Framework for Constructing Evidence-Sensitive Supervision

arXiv:2604.09537v1 Announce Type: cross Abstract: Evidence-grounded reasoning requires more than attaching retrieved text to a prediction: a model should make decisions that depend on whether the prov

Hardware

CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference

arXiv:2604.08584v1 Announce Type: cross Abstract: Long-context LLMs increasingly rely on extended, reusable prefill prompts for agents and domain Q&A, pushing attention and KV-cache to become the domi

hardwarearxiv-cs-ai

MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits

arXiv:2604.08952v1 Announce Type: new Abstract: Document Question Answering (DQA) involves generating answers from a document based on a user's query, representing a key task in document understanding

safetyarxiv-cs-cl

Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory

arXiv:2602.15313v2 Announce Type: replace Abstract: AI Memory, specifically how models organizes and retrieves historical messages, becomes increasingly valuable to Large Language Models (LLMs), yet e

Concepts

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conceptsmodelsindex

11 Apr 2026

Concepts

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11 Apr 2026

A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering

arXiv:2604.07274v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in medical question answering; however, purely parametric models often suffer from

Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Prediction

arXiv:2604.07659v1 Announce Type: new Abstract: Large language models (LLMs) hold significant promise for healthcare, yet their reliability in high-stakes clinical settings is often compromised by hal

Towards the Development of an LLM-Based Methodology for Automated Security Profiling in Compliance with Ukrainian Cybersecurity Regulations

arXiv:2604.06274v1 Announce Type: cross Abstract: In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to co

safetyarxiv-cs-ai

Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection

arXiv:2512.13040v2 Announce Type: replace-cross Abstract: Detecting fraud in financial transactions typically relies on tabular models that demand heavy feature engineering to handle high-dimensional

applicationsarxiv-cs-cl

Do Agents Need a New Kind of Paper? SPRA: Structured Paper Representation for Agents

arXiv:2610.21424v1 Announce Type: new Abstract: Scientific agents must connect research problems, methods, and findings dispersed through narrative articles. We introduce SPRA (Structured Paper Repres

researcharxiv-cs-ai

16 Oct 2026

Language Models Share a Readout Bottleneck in Working Memory

arXiv:2610.21176v1 Announce Type: cross Abstract: Large language models (LLMs) reproduce a human working-memory signature on the N-back task: performance declines as memory load N increases, and error

researcharxiv-cs-ai

16 Oct 2026

LLM-as-an-Investigator: Evidence-First Agentic Reasoning for Robust Interactive Problem Diagnosis

arXiv:2606.13220v2 Announce Type: replace Abstract: Large language models (LLMs) are used for technical troubleshooting, where problem descriptions are often incomplete and multiple causes can explain

16 Oct 2026

AI Representations of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups Using GPT-Based LLMs

arXiv:2610.16042v1 Announce Type: cross Abstract: The increasing use of artificial intelligence (AI) in mental health applications raises concerns about its potential to internalize and perpetuate soc

AtomSearch: Evidence-Grounded Tree Search for Agent Skill Optimization

arXiv:2610.19951v1 Announce Type: new Abstract: Agent skills adapt frozen models through editable external instructions. Revising several rules at once makes changes difficult to inspect, while judgin

DarKnight: Retrieval-Guided Agentic Framework for Breaking Dark Web CAPTCHA Gates

model-releasesarxiv-cs-cv

arXiv:2610.19830v1 Announce Type: cross Abstract: Cyber Threat Intelligence (CTI) investigators who monitor dark web marketplaces for leaked credentials and breach listings must pass the diverse CAPTC

FinGREAT: Evaluating LLMs on Financial Graph-guided Retrieval And Typing

model-releasesarxiv-cs-lg

arXiv:2610.19240v1 Announce Type: new Abstract: Financial disclosures express the underlying relationships of double-entry accounting through unstructured text. While financial LLM benchmarks predomin

HERO: Harnessing Evidence for Test-time Refinement and Prompt Optimization in Program Generation

arXiv:2610.19184v1 Announce Type: new Abstract: Harness optimization improves LLMs by refining reusable prompts and scaffolding, yet requires further adaptation for program generation tasks such as te