Search: “retrieval”

eOptShrinkQ: Near-Lossless KV Cache Compression Through Optimal Spectral Denoising and Quantization

model-releasesarxiv-cs-lg

arXiv:2605.02905v1 Announce Type: new Abstract: We show that the key-value (KV) cache in transformer attention heads admits a natural decomposition into a low-rank shared context component and a full-

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Research

From prompting to evidence-based translation: A RAG+prompt system for Japanese-Chinese translation and its pedagogical potential

DGX agent

arXiv:2605.03387v1 Announce Type: new Abstract: Large language models perform well on high-resource pairs but are less reliable for Japanese-Chinese sentences containing noun-modifying clause construc

researcharxiv-cs-cl

6 May 2026

KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation

arXiv:2605.01582v1 Announce Type: cross Abstract: Authoritative competency frameworks such as ESCO, ROME, and O*NET are essential for aligning education with labor market needs, yet their technical co

applicationsarxiv-cs-ai

Transformers with Selective Access to Early Representations

arXiv:2605.03953v1 Announce Type: cross Abstract: Several recent Transformer architectures expose later layers to representations computed in the earliest layers, motivated by the observation that low

researcharxiv-cs-cl

TriBench-Ko: Evaluating LLM Risks in Judicial Workflows

model-releasesarxiv-cs-cl

arXiv:2605.03792v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into legal workflows. However, existing benchmarks primarily address proxy tasks, such as bar e

Feedback-Normalized Developer Memory for Reinforcement-Learning Coding Agents: A Safety-Gated MCP Architecture

model-releasesarxiv-cs-cl

arXiv:2605.01567v1 Announce Type: cross Abstract: Large language model (LLM) coding agents increasingly operate over repositories, terminals, tests, and execution traces across long software-engineeri

GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing

arXiv:2605.02489v1 Announce Type: cross Abstract: As the ecosystem of Large Language Model (LLM)-based agents expands rapidly, efficient and accurate Agent Discovery becomes a critical bottleneck for

agentsarxiv-cs-cl

Seeing the Scene Matters: Revealing Forgetting in Video Understanding Models with a Scene-Aware Long-Video Benchmark

arXiv:2603.27259v2 Announce Type: replace Abstract: Long video understanding (LVU) remains a core challenge in multimodal learning. Although recent vision-language models (VLMs) have made notable prog

SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms

arXiv:2605.00043v1 Announce Type: cross Abstract: Big data platforms are widely used in modern enterprises, and an in-production intelligent assistant is increasingly important to help users quickly f

agentsarxiv-cs-ai

Zero-Shot Confidence Estimation for Small LLMs: When Supervised Baselines Aren't Worth Training

arXiv:2605.02241v1 Announce Type: cross Abstract: How reliably can a small language model estimate its own correctness? The answer determines whether local-to-cloud routing-escalating queries a cheap

local-aiarxiv-cs-cl

Agentic AI for Substance Use Education: Integrating Regulatory and Scientific Knowledge Sources

arXiv:2605.00383v1 Announce Type: new Abstract: The delivery of traditional substance education has remained problematic due to challenges in scalability, personalization, and the currency of informat

agentsarxiv-cs-cl

Geometric analysis of attractor boundaries and storage capacity limits in kernel Hopfield networks

arXiv:2605.00366v1 Announce Type: cross Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit strong storage capabilities, but the dynamical and geometric mech

applicationsarxiv-cs-lg

MemRouter: Memory-as-Embedding Routing for Long-Term Conversational Agents

arXiv:2605.00356v1 Announce Type: new Abstract: Long-term conversational agents must decide which turns to store in external memory, yet recent systems rely on autoregressive LLM generation at every t

safetyarxiv-cs-cl

Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning

arXiv:2605.00265v1 Announce Type: new Abstract: Real-world knowledge is often organized as hierarchies such as product taxonomies, medical ontologies, and label trees, yet learning hierarchical repres

local-aiarxiv-cs-lg

Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression

model-releasesarxiv-cs-lg

arXiv:2604.28109v1 Announce Type: new Abstract: Model merging has attracted attention as an effective path toward multi-task adaptation by integrating knowledge from multiple task-specific models. Amo

In Line with Context: Repository-Level Code Generation via Context Inlining

arXiv:2601.00376v2 Announce Type: replace-cross Abstract: Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model

One Single Hub Text Breaks CLIP: Identifying Vulnerabilities in Cross-Modal Encoders via Hubness

arXiv:2604.27674v1 Announce Type: cross Abstract: The hubness problem, in which hub embeddings are close to many unrelated examples, occurs often in high-dimensional embedding spaces and may pose a pr

Understanding and Improving Length Generalization in Hierarchical Sparse Attention Models

arXiv:2510.17196v3 Announce Type: replace-cross Abstract: Effectively processing long contexts is a critical challenge for language models. While standard Transformers are limited by quadratic complex

3D-LENS: A 3D Lifting-based Elevated Novel-view Synthesis method for Single-View Aerial-Ground Re-Identification

arXiv:2604.26520v1 Announce Type: new Abstract: Aerial-Ground Re-Identification (AG-ReID) is constrained by the viewpoint-domain gap, as drastic viewpoint disparities occlude or distort discriminative

A Multistage Extraction Pipeline for Long Scanned Financial Documents: An Empirical Study in Industrial KYC Workflows

arXiv:2604.26462v1 Announce Type: new Abstract: Structured information extraction from long, multilingual scanned financial documents is a core requirement in industrial KYC and compliance workflows.

AdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue Agents

model-releasesarxiv-cs-cl

arXiv:2603.16496v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step

From Intent to Evidence: A Categorical Approach for Structural Evaluation of Deep Research Agents

model-releasesarxiv-cs-lg

arXiv:2603.25342v2 Announce Type: replace Abstract: Deep Research Agents (DRAs) aim to answer complex questions by searching the web, checking evidence, and synthesizing conclusions across heterogeneo

Glance-or-Gaze: Incentivizing LMMs to Adaptively Focus Search via Reinforcement Learning

arXiv:2601.13942v2 Announce Type: replace-cross Abstract: Large Multimodal Models (LMMs) have achieved remarkable success in visual understanding, yet they struggle with knowledge-intensive queries in

safetyarxiv-cs-ai

Stress Testing Factual Consistency Metrics for Long-Document Summarization

arXiv:2511.07689v2 Announce Type: replace-cross Abstract: Evaluating the factual consistency of abstractive text summarization remains a significant challenge, particularly for long documents, where c

DouC: Dual-Branch CLIP for Training-Free Open-Vocabulary Segmentation

arXiv:2604.24997v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation requires assigning pixel-level semantic labels while supporting an open and unrestricted set of categories. Traini

local-aiarxiv-cs-cv

DualGeo: A Dual-View Framework for Worldwide Image Geo-localization

arXiv:2604.25533v1 Announce Type: new Abstract: Worldwide image geo-localization aims to infer the geographic location of an image captured anywhere on Earth, spanning street, city, regional, national

researcharxiv-cs-cv

M^3-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering

arXiv:2604.25122v1 Announce Type: new Abstract: We present M^3-VQA, a novel knowledge-based Visual Question Answering (VQA) benchmark, to enhance the evaluation of multimodal large language models (ML

Measuring the stability and plasticity of recommender systems

arXiv:2508.03941v3 Announce Type: replace-cross Abstract: The typical offline protocol to evaluate recommendation algorithms is to collect a dataset of user-item interactions and then use a part of th

researcharxiv-cs-lg

MMLANDMARKS: a Cross-View Instance-Level Benchmark for Geo-Spatial Understanding

arXiv:2512.17492v2 Announce Type: replace Abstract: Geo-spatial analysis of our world benefits from a multimodal approach, as every single geographic location can be described in numerous ways (images

OmniVTG: A Large-Scale Dataset and Training Paradigm for Open-World Video Temporal Grounding

arXiv:2604.25276v1 Announce Type: new Abstract: Video Temporal Grounding (VTG), the task of localizing video segments from text queries, struggles in open-world settings due to limited dataset scale a

local-aiarxiv-cs-cv

SARE: Sample-wise Adaptive Reasoning for Training-free Fine-grained Visual Recognition

arXiv:2603.17729v3 Announce Type: replace Abstract: Recent advances in Large Vision-Language Models (LVLMs) have enabled training-free Fine-Grained Visual Recognition (FGVR). However, effectively expl

SciDER: Scientific Data-centric End-to-end Researcher

arXiv:2603.01421v2 Announce Type: replace-cross Abstract: Automated scientific discovery with large language models is transforming the research lifecycle from ideation to experimentation, yet existin

agentsarxiv-cs-cl

Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspective

arXiv:2603.14248v2 Announce Type: replace-cross Abstract: Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizo

researcharxiv-cs-cl

Tutorials

2D Pre-Training for 3D Pose Estimation

arXiv:2604.22830v1 Announce Type: new Abstract: Pre-training is a general method that is used in a range of deep learning tasks. By first training a model on one task, and then further training on the

tutorialsarxiv-cs-cv

Au-M-ol: A Unified Model for Medical Audio and Language Understanding

arXiv:2604.23284v1 Announce Type: cross Abstract: In this work, we present Au-M-ol, a novel multimodal architecture that extends Large Language Models (LLMs) with audio processing. It is designed to i

applicationsarxiv-cs-ai

BEAR: Towards Beam-Search-Aware Optimization for Recommendation with Large Language Models

arXiv:2601.22925v2 Announce Type: replace-cross Abstract: Recent years have seen a rapid surge in research leveraging Large Language Models (LLMs) for recommendation. These methods typically employ su

applicationsarxiv-cs-ai

Behavioral Intelligence Platforms: From Event Streams to Autonomous Insight via Probabilistic Journey Graphs, Behavioral Knowledge Extraction, and Grounded Language Generation

arXiv:2604.22762v1 Announce Type: cross Abstract: Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, b

agentsarxiv-cs-ai

Benchmarking Source-Sensitive Reasoning in Turkish: Humans and LLMs under Evidential Trust Manipulation

arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit

local-aiarxiv-cs-ai

Beyond the Attention Stability Boundary: Agentic Self-Synthesizing Reasoning Protocols

arXiv:2604.24512v1 Announce Type: new Abstract: As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging

arXiv:2604.22989v1 Announce Type: cross Abstract: Recent medical multimodal foundation models are built as multimodal LLMs (MLLMs) by connecting a CLIP-pretrained vision encoder to an LLM using LLaVA-

CorpusQA: A 10 Million Token Benchmark for Corpus-Level Analysis and Reasoning

arXiv:2601.14952v2 Announce Type: replace-cross Abstract: While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largel

Evaluating the Search Agent in a Parallel World

arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev

From Similarity to Structure: Training-free LLM Context Compression with Hybrid Graph Priors

arXiv:2604.23277v1 Announce Type: cross Abstract: Long-context large language models remain computationally expensive to run and often fail to reliably process very long inputs, which makes context co

Hard to See, Hard to Label: Generative and Symbolic Acquisition for Subtle Visual Phenomena

arXiv:2604.22990v1 Announce Type: cross Abstract: Subtle visual anomalies such as hairline cracks, sub-millimeter voids, and low-contrast inclusions are structurally atypical yet visually ambiguous, m

KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning

arXiv:2604.22779v1 Announce Type: cross Abstract: Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucination

agentsarxiv-cs-ai

LAVA: Layered Audio-Visual Anti-tampering Watermarking for Robust Deepfake Detection and Localization

arXiv:2604.23957v1 Announce Type: new Abstract: Proactive watermarking offers a promising approach for deepfake tamper detection and localization in short-form videos. However, existing methods often

safetyarxiv-cs-cv

Learning from the Best: Smoothness-Driven Metrics for Data Quality in Imitation Learning

arXiv:2604.23000v1 Announce Type: new Abstract: In behavioral cloning (BC), policy performance is fundamentally limited by demonstration data quality. Real-world datasets contain trajectories of varyi

safetyarxiv-cs-ro

Less is More in Semantic Space: Intrinsic Decoupling via Clifford-M for Fundus Image Classification

arXiv:2603.20806v2 Announce Type: replace Abstract: Multi-label fundus diagnosis requires features that capture both fine-grained lesions and large-scale retinal structure. Many multi-scale medical vi

safetyarxiv-cs-cv