Search: “retrieval”

arXiv:2603.05207v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge. However, existing vector-based method

applicationsarxiv-cs-cl

CourseTimeQA: A Lecture-Video Benchmark and a Latency-Constrained Cross-Modal Fusion Method for Timestamped QA

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2512.00360v2 Announce Type: replace Abstract: We study timestamped question answering over educational lecture videos under a single-GPU latency/memory budget. Given a natural-language query, th

model-releasesarxiv-cs-cl

3 Jun 2026

Diagnosing Knowledge Gaps in LLM Tool Use: An Agentic Benchmark for Novel API Acquisition

arXiv:2606.03657v1 Announce Type: new Abstract: Large language models for code generation often need to use APIs that are absent from their pretraining data. This requires more than recalling a functi

G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation

arXiv:2606.03078v1 Announce Type: new Abstract: Effective document-level machine translation (DocMT) requires capturing long-range discourse dependencies. Recent work has explored retrieval-based and

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection

arXiv:2606.02812v1 Announce Type: new Abstract: Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequ

Diagnosing LLM Arbitration Behavior over Pre-evidence Epistemic States in RAG-based Fact-Checking

arXiv:2606.01120v1 Announce Type: new Abstract: In RAG-based fact-checking, LLMs are increasingly used as verifiers to check given claims against retrieved evidence. Their parametric knowledge can ind

Forget Attention: Importance-Aware Attention Is All You Need

arXiv:2606.02332v1 Announce Type: new Abstract: Combining attention's global retrieval with the sequential importance signal of state space models (SSMs) is the open challenge of hybrid language model

MyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding

arXiv:2606.00174v1 Announce Type: cross Abstract: Electromyography (EMG) directly reflects muscle activation and is a key sensing modality for gesture recognition, prosthetic control, and wearable int

REBot: From RAG to CatRAG with Semantic Enrichment and Graph Routing

arXiv:2510.01800v3 Announce Type: replace Abstract: Academic regulation advising is essential for helping students interpret and comply with institutional policies, yet building effective systems requ

TVIR: Building Deep Research Agents Towards Text--Visual Interleaved Report Generation

arXiv:2606.02320v1 Announce Type: new Abstract: Deep Research Agents have shown strong capability in multi-step information retrieval, reasoning, and long-form report generation, but existing benchmar

Local Ai

An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations

arXiv:2605.30604v1 Announce Type: cross Abstract: Regulated cybersecurity workflows lack a runtime substrate that enforces organization-level scope across retrieval, tool calls, memory, findings, repo

local-aiarxiv-cs-ai

1 Jun 2026

ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents

arXiv:2605.30712v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in reasoning, tool use, and multi-step interaction, but they often solve tasks from scr

1 Jun 2026

Query-focused and Memory-aware Reranker for Long Context Processing

arXiv:2602.12192v3 Announce Type: replace Abstract: Built upon the existing analysis of retrieval heads in large language models, we propose an alternative reranking framework that trains models to es

1 Jun 2026

Efficient Test-Time Finetuning of LLMs via Convex Reconstruction and Gradient Caching

arXiv:2605.30337v1 Announce Type: new Abstract: Test-time finetuning (TTFT) is a rapidly evolving paradigm that adapts a language model to each prompt by retrieving related sequences, updating the mod

researcharxiv-cs-lg

GrepSeek: Training Search Agents for Direct Corpus Interaction

arXiv:2605.29307v1 Announce Type: cross Abstract: Large Language Model (LLM) search agents have shown strong promise for knowledge-intensive language tasks through multiple rounds of reasoning and inf

Less Is More: Elevating RAG via Performance-Driven Context Compression

arXiv:2508.19282v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm for improving the timeliness of knowledge updates and the factual acc

Rethinking Literature Search Evaluation: Deep Research Helps, and Human Citation Lists Are Not a Ground Truth

arXiv:2605.29234v1 Announce Type: new Abstract: We study large-scale literature search from two complementary angles: improving the retrieval pipeline, and stress-testing the human reference list as a

Local Ai

S3Mem: Structured Spatiotemporal Scene-Event Memory for Long-Horizon Interactive Question Answering

arXiv:2605.28831v1 Announce Type: cross Abstract: Long-horizon interactive agents often accumulate large trajectory histories yet still fail to answer questions about earlier events reliably. We argue

local-aiarxiv-cs-ai

A Fixed-Budget, Cluster-Aware Standard for LLM-as-a-Judge Evaluation: A Multi-Hop RAG Stress Test

arXiv:2605.27789v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems are often compared by asking a large language model (LLM) judge which answer is better. For multi-hop RAG,

Analyzing Quality-Latency-Resource Trade-offs in a Technical Documentation RAG Assistant Using LoRA Adaptation

arXiv:2605.28222v1 Announce Type: new Abstract: We study quality-latency-resource trade-offs in a documentation-grounded retrieval-augmented generation (RAG) system that uses Low-Rank Adaptation (LoRA

ConvMemory: A Lightweight Learned Memory Reranker, a Negative Attribution Result, and a Research-Preview Conflict Editor

arXiv:2605.28062v1 Announce Type: new Abstract: We describe ConvMemory, a small 3.6M-parameter learned reranker for conversational long-term memory retrieval, trained with cross-encoder teacher superv

Applications

GraphSteal: Structural Knowledge Stealing from Graph RAG via Traversal Reconstruction

arXiv:2605.28645v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances LLMs by grounding generation in query-relevant external evidence. Beyond unstructured text corpora, Grap

applicationsarxiv-cs-cl

AI Agent for Reverse-Engineering Legacy Finite-Difference Code and Translating to Devito

arXiv:2601.18381v2 Announce Type: replace Abstract: To facilitate the transformation of legacy finite difference implementations into the Devito environment, this study develops an integrated AI agent

27 May 2026

Cordon-MAS: Defending RAG against Knowledge Poisoning via Information-Flow Control

arXiv:2605.26754v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) increasingly underpins high-stakes applications, yet remains vulnerable to Confundo-style poisoning where adversa

27 May 2026

AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora

arXiv:2605.25382v1 Announce Type: new Abstract: Evidence construction systems--chunk retrieval, agent memory, knowledge-graph traversal, and thematic indexing--are evaluated on separate benchmarks wit

Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning

arXiv:2508.19113v3 Announce Type: replace Abstract: Large reasoning models (LRMs) combined with retrieval-augmented generation (RAG) have enabled deep research agents capable of multi-step reasoning w

Local Ai

Lngram: N-gram Conditional Memory in Latent Space

arXiv:2605.24869v1 Announce Type: new Abstract: Sequence modeling requires both compositional reasoning and local static knowledge retrieval, yet standard Transformers handle both through dense comput

local-aiarxiv-cs-cl

Peak-Then-Collapse and the Four Interface Channels of Knowledge-Graph Tool Use

arXiv:2605.26037v1 Announce Type: new Abstract: We test the standard RLVR tool-use recipe -- GRPO on Qwen2.5-7B-Instruct -- on a deliberately minimal knowledge-graph tool API: four Freebase navigation

safetyarxiv-cs-cl

UniRank: End-to-End Domain-Specific Reranking of Hybrid Text-Image Candidates

arXiv:2603.29897v2 Announce Type: replace-cross Abstract: Reranking is a critical component in many information retrieval pipelines. Despite remarkable progress in text-only settings, multimodal reran

Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models

arXiv:2602.10538v3 Announce Type: replace-cross Abstract: Agentic theorem provers combine a reasoning model, retrieval, search, and a proof assistant verifier, yet it remains unclear which components

agentsarxiv-cs-lg

Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning

arXiv:2509.26383v5 Announce Type: replace-cross Abstract: Knowledge-graph retrieval-augmented generation (KG-RAG) couples large language models (LLMs) with structured, verifiable knowledge graphs (KGs

25 May 2026

MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection

arXiv:2605.23723v1 Announce Type: new Abstract: Large language model agents increasingly rely on persistent memory to store past interactions, retrieve relevant demonstrations, and improve long-horizo

25 May 2026

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen

25 May 2026

Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling

arXiv:2605.22484v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at tasks like zero-shot classification and cross-modal retrieval by mapping images and text to a shared space, but t

safetyarxiv-cs-cv

22 May 2026

Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses

arXiv:2605.19229v1 Announce Type: new Abstract: Survey research faces mounting structural challenges: declining response rates, sample bias, block-wise missingness among at-risk respondents, and AI-as

PASC: Pipeline-Aware Conformal Prediction with Joint Coverage Guarantees for Multi-Stage NLP and LLM Pipelines

arXiv:2605.18812v1 Announce Type: cross Abstract: Modern NLP and LLM systems are pipelines: named entity recognition (NER) -> entity disambiguation (NED) -> entity typing, retrieval-augmented generati

agentsarxiv-cs-cl

Rethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent Memory

arXiv:2605.19952v1 Announce Type: new Abstract: To enable reliable long-term interaction, LLM agents require a memory system that can faithfully store, efficiently retrieve, and deeply reason over acc

Trust or Abstain? A Self-Aware RAG Approach

arXiv:2605.18792v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves large language models (LLMs) by incorporating external evidence, but it also introduces knowledge confli

AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning

arXiv:2605.18592v1 Announce Type: cross Abstract: Rubric-based reward shaping is an effective method for fine-tuning LLMs via RL, where structured rubrics decompose standard outcome rewards into multi

Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents

arXiv:2605.17641v1 Announce Type: new Abstract: Long-horizon LLM agents rely on persistent memory to support interactions across sessions, yet existing memory systems often retrieve context using sema

InfoFlow: A Framework for Multi-Layer Transformer Analysis

model-releasesarxiv-cs-lg

arXiv:2605.17930v1 Announce Type: new Abstract: While the approximation properties of single-layer Transformer architectures have been studied in recent works, a rigorous theoretical understanding of

Tools

Introducing the Ettin Reranker Family

The Ettin Reranker Family represents a new suite of reranking models released on Hugging Face designed to improve retrieval-augmented generation (RAG) systems by reordering search results based on rel

toolshugging-face

LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots

arXiv:2605.16474v1 Announce Type: cross Abstract: The integration of advertising auction mechanisms into large language model (LLM)-based chatbots presents a significant opportunity for commercializat

PriHA: A RAG-Enhanced LLM Framework for Primary Healthcare Assistant in Hong Kong

arXiv:2604.14215v2 Announce Type: replace-cross Abstract: To address the unsustainable rise in public health expenditures, the Hong Kong SAR Government is shifting its strategic focus to primary healt

Prior Knowledge Makes It Possible: From Sublinear Graph Algorithms to LLM Test-Time Methods

arXiv:2510.16609v3 Announce Type: replace-cross Abstract: Test-time augmentation, such as Retrieval-Augmented Generation (RAG) or tool use, critically depends on an interplay between a model's paramet

CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency

arXiv:2512.00417v5 Announce Type: replace Abstract: This paper introduces CryptoBench, the first expert-curated, dynamic benchmark designed to rigorously evaluate the real-world capabilities of Large

18 May 2026

Generative Long-term User Interest Modeling for Click-Through Rate Prediction

arXiv:2605.15905v1 Announce Type: cross Abstract: Modeling long-term user interests with massive historical user behaviors enhances click-through rate (CTR) prediction performance in advertising and r

18 May 2026

GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective