Search: “retrieval”

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

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Model Releases

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

DGX agent

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

model-releasesarxiv-cs-ai

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

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,

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

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

Knowledge Capsules: Structured Nonparametric Memory Units for LLMs

arXiv:2604.20487v1 Announce Type: cross Abstract: Large language models (LLMs) encode knowledge in parametric weights, making it costly to update or extend without retraining. Retrieval-augmented gene

Memory-Augmented LLM-based Multi-Agent System for Automated Feature Generation on Tabular Data

arXiv:2604.20261v1 Announce Type: new Abstract: Automated feature generation extracts informative features from raw tabular data without manual intervention and is crucial for accurate, generalizable

agentsarxiv-cs-ai

SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition

arXiv:2604.20146v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving

local-aiarxiv-cs-cl

Semantic Recall for Vector Search

arXiv:2604.20417v1 Announce Type: cross Abstract: We introduce Semantic Recall, a novel metric to assess the quality of approximate nearest neighbor search algorithms by considering only semantically

SkillGraph: Graph Foundation Priors for LLM Agent Tool Sequence Recommendation

arXiv:2604.19793v1 Announce Type: new Abstract: LLM agents must select tools from large API libraries and order them correctly. Existing methods use semantic similarity for both retrieval and ordering

SweRank: Software Issue Localization with Code Ranking

arXiv:2505.07849v2 Announce Type: replace-cross Abstract: Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language

To Know is to Construct: Schema-Constrained Generation for Agent Memory

arXiv:2604.20117v1 Announce Type: new Abstract: Constructivist epistemology argues that knowledge is actively constructed rather than passively copied. Despite the generative nature of Large Language

Construction of Knowledge Graph based on Language Model

arXiv:2604.19137v1 Announce Type: new Abstract: Knowledge Graph (KG) can effectively integrate valuable information from massive data, and thus has been rapidly developed and widely used in many field

22 Apr 2026

Althea: Human-AI Collaboration for Fact-Checking and Critical Reasoning

arXiv:2602.11161v2 Announce Type: replace-cross Abstract: The web's information ecosystem demands fact-checking systems that are both scalable and epistemically trustworthy. Automated approaches offer

Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs

arXiv:2510.00861v2 Announce Type: replace Abstract: While search-augmented large language models (LLMs) exhibit impressive capabilities, their reliability in complex multi-hop reasoning remains limite

LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations

arXiv:2509.12539v2 Announce Type: replace-cross Abstract: We present LEAF ('Lightweight Embedding Alignment Framework'), a knowledge distillation framework for text embedding models. A key distinguish

OASIS: On-Demand Hierarchical Event Memory for Streaming Video Reasoning

arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a

researcharxiv-cs-cv

VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning

arXiv:2601.15724v2 Announce Type: replace Abstract: Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning

local-aiarxiv-cs-cv

Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception

arXiv:2604.17475v1 Announce Type: cross Abstract: Small Vision-Language Models (SVLMs) are efficient task controllers but often suffer from visual brittleness and poor tool orchestration. They typical

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec

agentsarxiv-cs-cl

Faster LLM Inference via Sequential Monte Carlo

arXiv:2604.15672v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates language model inference by drafting tokens from a cheap proposal model and verifying them against an expensive

20 Apr 2026

FD-NL2SQL: Feedback-Driven Clinical NL2SQL that Improves with Use

arXiv:2604.15646v1 Announce Type: new Abstract: Clinicians exploring oncology trial repositories often need ad-hoc, multi-constraint queries over biomarkers, endpoints, interventions, and time, yet wr

20 Apr 2026

Tutorials

A Pythonic Functional Approach for Semantic Data Harmonisation in the ILIAD Project

arXiv:2604.13042v1 Announce Type: cross Abstract: Semantic data harmonisation is a central requirement in the ILIAD project, where heterogeneous environmental data must be harmonised according to the

tutorialsarxiv-cs-ai

Blinded Multi-Rater Comparative Evaluation of a Large Language Model and Clinician-Authored Responses in CGM-Informed Diabetes Counseling

arXiv:2604.15124v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) is central to diabetes care, but explaining CGM patterns clearly and empathetically remains time-intensive. Evidence

Tutorials

CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding

arXiv:2601.21262v3 Announce Type: replace Abstract: Although Multimodal Large Language Models (MLLMs) have shown remarkable potential in Visual Document Retrieval (VDR) through generating high-quality

tutorialsarxiv-cs-cl

From Tokens to Steps: Verification-Aware Speculative Decoding for Efficient Multi-Step Reasoning

arXiv:2604.15244v1 Announce Type: new Abstract: Speculative decoding (SD) accelerates large language model inference by allowing a lightweight draft model to propose outputs that a stronger target mod

A Proactive EMR Assistant for Doctor-Patient Dialogue: Streaming ASR, Belief Stabilization, and Preliminary Controlled Evaluation

arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the

Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning

arXiv:2601.13115v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through na

agentsarxiv-cs-cl

GeoBridge: A Semantic-Anchored Multi-View Foundation Model Bridging Images and Text for Geo-Localization

model-releasesarxiv-cs-cv

arXiv:2512.02697v3 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images that visually correspond to a query image. However, the trad

MM-Doc-R1: Training Agents for Long Document Visual Question Answering through Multi-turn Reinforcement Learning

arXiv:2604.13579v1 Announce Type: new Abstract: Conventional Retrieval-Augmented Generation (RAG) systems often struggle with complex multi-hop queries over long documents due to their single-pass ret

CLEAR: Cross-Lingual Enhancement in Alignment via Reverse-training

arXiv:2604.05821v2 Announce Type: replace Abstract: Existing multilingual embedding models often encounter challenges in cross-lingual scenarios due to imbalanced linguistic resources and less conside

Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training

arXiv:2604.12967v1 Announce Type: new Abstract: Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches

safetyarxiv-cs-ai

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

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

Human-Inspired Context-Selective Multimodal Memory for Social Robots

arXiv:2604.12081v1 Announce Type: new Abstract: Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the con

MoDora: Tree-Based Semi-Structured Document Analysis System

arXiv:2602.23061v3 Announce Type: replace-cross Abstract: Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and

local-aiarxiv-cs-ai

TRUST Agents: A Collaborative Multi-Agent Framework for Fake News Detection, Explainable Verification, and Logic-Aware Claim Reasoning

arXiv:2604.12184v1 Announce Type: new Abstract: TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a