Search: “retrieval”

RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

arXiv:2605.16045v1 Announce Type: cross Abstract: Memory systems often organize user-agent interactions as retrievable external memory and are crucial for long-running agents by overcoming the limited

18 May 2026

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Model Releases

SkyLink: A Large Vision-Language Model Driven Re-ranking Framework for Cross-View UAV geolocalization

DGX agent

arXiv:2603.08063v3 Announce Type: replace Abstract: Cross-view UAV geolocalization is fundamentally a challenging large-scale image retrieval task, aiming to determine the geographic coordinates of Un

model-releasesarxiv-cs-cv

18 May 2026

CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications

arXiv:2602.17949v2 Announce Type: replace-cross Abstract: Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifier

Latency-Quality Routing for Functionally Equivalent Tools in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.14241v1 Announce Type: new Abstract: Tool-augmented LLM agents increasingly access the same tool type through multiple functionally equivalent providers, such as web-search APIs, retrievers

RAG - Recherche Documentaire

Retrieval-Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by enabling them to access and utilize external knowledge sources during response generation. This likely

local-air-ollama

SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification

arXiv:2504.09549v3 Announce Type: replace Abstract: Aerial-Ground Person Re-IDentification (AG-ReID) aims to retrieve specific persons across cameras with different viewpoints. Previous works focus on

researcharxiv-cs-cv

Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG

arXiv:2605.15109v1 Announce Type: new Abstract: Retrieval-Augmented Generation can improve factuality by grounding answers in external evidence, but Agentic GraphRAG complicates what it means for cita

GAAMA: Graph Augmented Associative Memory for Agents

arXiv:2603.27910v2 Announce Type: replace Abstract: AI agents that interact with users across multiple sessions require persistent long-term memory to maintain coherent, personalized behavior. Current

14 May 2026

Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context

arXiv:2605.13831v1 Announce Type: new Abstract: Long-context modeling is becoming a core capability of modern large vision-language models (LVLMs), enabling sustained context management across long-do

agentsarxiv-cs-cv

14 May 2026

Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification

arXiv:2603.28488v2 Announce Type: replace Abstract: Large language models (LLMs) remain unreliable for high-stakes claim verification due to hallucinations and shallow reasoning. While retrieval-augme

13 May 2026

Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection

arXiv:2605.12156v1 Announce Type: new Abstract: Automatic misinformation detection performs well when deception is visible in what an article explicitly states. However, some misinformation articles r

13 May 2026

ASTRA-QA: A Benchmark for Abstract Question Answering over Documents

arXiv:2605.10168v1 Announce Type: new Abstract: Document-based question answering (QA) increasingly includes abstract questions that require synthesizing scattered information from long documents or a

Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning

arXiv:2605.08271v1 Announce Type: cross Abstract: Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For

CoCoDA: Co-evolving Compositional DAG for Tool-Augmented Agents

arXiv:2605.08399v1 Announce Type: new Abstract: Tool-augmented language models can extend small language models with external executable skills, but scaling the tool library creates a coupled challeng

Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support

arXiv:2605.09534v1 Announce Type: cross Abstract: Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding age

safetyarxiv-cs-ai

HAGE: Harnessing Agentic Memory via RL-Driven Weighted Graph Evolution

arXiv:2605.09942v1 Announce Type: new Abstract: Memory retrieval in agentic large language model (LLM) systems is often treated as a static lookup problem, relying on flat vector search or fixed binar

Merlin: Deterministic Byte-Exact Deduplication for Lossless Context Optimization in Large Language Model Inference

arXiv:2605.09990v1 Announce Type: new Abstract: Data-intensive applications, ranging from large-scale retrieval systems to advanced data pipelines, are increasingly bottlenecked by the processing of h

local-aiarxiv-cs-cl

PRISM: Fast Online LLM Serving via Scheduling-Memory Co-design

arXiv:2605.08581v1 Announce Type: new Abstract: Modern online large language model (LLM) services, such as Retrieval-Augmented Generation (RAG) and agent systems, increasingly expose two prominent cha

agentsarxiv-cs-lg

The First Drop of Ink: Nonlinear Impact of Misleading Information in Long-Context Reasoning

arXiv:2605.10828v1 Announce Type: new Abstract: As large language models are increasingly deployed in retrieval-augmented generation and agentic systems that accumulate extensive context, understandin

TrajPrism: A Multi-Task Benchmark for Language-Grounded Urban Trajectory Understanding

arXiv:2605.10782v1 Announce Type: new Abstract: Urban mobility is naturally expressed both as trajectories in space and as natural-language descriptions of travel intent, constraints, and preferences.

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems

arXiv:2506.04565v2 Announce Type: replace-cross Abstract: Compound AI Systems (CAIS) are an emerging paradigm that integrates large language models (LLMs) with external components, including retriever

11 May 2026

Multi-Level Bidirectional Biomimetic Learning for EEG-Based Visual Decoding

arXiv:2605.04680v1 Announce Type: new Abstract: EEG-based visual neural decoding aims to align neural responses with visual stimuli for tasks such as image retrieval. However, limited paired data and

safetyarxiv-cs-cv

7 May 2026

Understanding Transformers through the Lens of Pavlovian Conditioning

arXiv:2508.08289v2 Announce Type: replace Abstract: Transformer architectures have revolutionized artificial intelligence (AI) through their attention mechanisms, yet the computational principles unde

researcharxiv-cs-lg

7 May 2026

Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

arXiv:2603.01486v2 Announce Type: replace Abstract: Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where conte

6 May 2026

On the Privacy of LLMs: An Ablation Study

arXiv:2605.02255v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in interactive and retrieval-augmented settings, raising significant privacy concerns. While at

6 May 2026

VL-SAM-v3: Memory-Guided Visual Priors for Open-World Object Detection

arXiv:2605.03456v1 Announce Type: new Abstract: Open-world object detection aims to localize and recognize objects beyond a fixed closed-set label space. It is commonly divided into two categories, i.

local-aiarxiv-cs-cv

6 May 2026

Toward a Scientific Discovery Engine for Weather and Climate Data: A Visual Analytics Workbench for Embedding-Based Exploration

arXiv:2605.00972v1 Announce Type: cross Abstract: Earth system science is producing increasingly large, high-dimensional datasets from physics based Earth system models to AI-based weather and climate

safetyarxiv-cs-cv

5 May 2026

CleanBase: Detecting Malicious Documents in RAG Knowledge Databases

arXiv:2605.00460v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is vulnerable to prompt injection attacks, in which an adversary inserts malicious documents containing carefully

researcharxiv-cs-lg

4 May 2026

Tools

Pinecone Nexus: The Knowledge Engine for Agents

Pinecone Nexus is a knowledge infrastructure platform designed to enable AI agents to access, retrieve, and reason over enterprise data at scale. The system addresses the challenge of integrating larg

toolspinecone

4 May 2026

SIMON: Saliency-aware Integrative Multi-view Object-centric Neural Decoding

arXiv:2605.00401v1 Announce Type: new Abstract: Recent EEG-to-image retrieval methods leverage pretrained vision encoders and foveation-inspired priors, but typically assume a fixed, center-focused vi

safetyarxiv-cs-cv

4 May 2026

Not All Memories Age the Same: Autodiscovery of Adaptive Decay in Knowledge Graphs

arXiv:2604.26970v1 Announce Type: cross Abstract: Knowledge graphs used for retrieval treat all facts as equally current. Existing temporal approaches apply uniform decay, using a single forgetting cu

1 May 2026

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

1 May 2026

CogRAG+: Cognitive-Level Guided Diagnosis and Remediation of Memory and Reasoning Deficiencies in Professional Exam QA

arXiv:2604.25928v1 Announce Type: new Abstract: Professional domain knowledge underpins human civilization, serving as both the basis for industry entry and the core of complex decision-making and pro

30 Apr 2026

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent

arXiv:2604.26197v1 Announce Type: cross Abstract: Large Language Model (LLM) agents are increasingly used in real-world products, where personalized and context-aware user interactions are essential.

agentsarxiv-cs-lg

30 Apr 2026

GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity.

researcharxiv-cs-cv

29 Apr 2026

2nd of the 5th PVUW MeViS-Audio Track: ASR-SaSaSa2VA

arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap

local-aiarxiv-cs-cv

CLIN-LLM: A Safety-Constrained Hybrid Framework for Clinical Diagnosis and Treatment Generation

arXiv:2510.22609v2 Announce Type: replace Abstract: Accurate symptom-to-disease classification and clinically grounded treatment recommendations remain challenging, particularly in heterogeneous patie

Applications

CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning

arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr

applicationsarxiv-cs-ai

Tutorials

Learning to Route Queries to Heads for Attention-based Re-ranking with Large Language Models

arXiv:2604.24608v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently been explored as fine-grained zero-shot re-rankers by leveraging attention signals to estimate document rel

tutorialsarxiv-cs-ai

Making Dialogue Grounding Data Rich: A Three-Tier Data Synthesis Framework for Generalized Referring Expression Comprehension

arXiv:2512.02791v2 Announce Type: replace Abstract: Dialogue-Based Generalized Referring Expression Comprehension (GREC) requires models to ground the expression and unlimited targets in complex visua

most personal rag setups for ollama feed it the wrong corpus

Based on the Reddit post title, this entry likely discusses common mistakes and pitfalls in setting up personal Retrieval-Augmented Generation (RAG) systems with Ollama, specifically focusing on incor

local-air-ollama

25 Apr 2026

CI-Work: Benchmarking Contextual Integrity in Enterprise LLM Agents

arXiv:2604.21308v1 Announce Type: cross Abstract: Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a us

It's High Time: A Survey of Temporal Question Answering

arXiv:2505.20243v4 Announce Type: replace Abstract: Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Tempo

Revisiting Content-Based Music Recommendation: Efficient Feature Aggregation from Large-Scale Music Models

arXiv:2604.20847v1 Announce Type: cross Abstract: Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking

SlideAgent: Hierarchical Agentic Framework for Multi-Page Visual Document Understanding

arXiv:2510.26615v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but it must balance limited effective context, re

All Languages Matter: Understanding and Mitigating Language Bias in Multilingual RAG

arXiv:2604.20199v1 Announce Type: new Abstract: Multilingual Retrieval-Augmented Generation (mRAG) leverages cross-lingual evidence to ground Large Language Models (LLMs) in global knowledge. However,

safetyarxiv-cs-cl

23 Apr 2026

Context Attribution with Multi-Armed Bandit Optimization

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

23 Apr 2026

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering

arXiv:2604.20531v1 Announce Type: new Abstract: This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazak