Search: “framework”

UAV as Urban Construction Change Monitor: A New Benchmark and Change Captioning Model

arXiv:2605.04409v1 Announce Type: new Abstract: Remote Sensing Image Change Captioning (RSICC) aims to generate spatially grounded natural language descriptions of scene evolution from bi-temporal ima

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ULF-Loc: Unbiased Landmark Feature for Robust Visual Localization with 3D Gaussian Splatting

DGX agent

arXiv:2605.04730v1 Announce Type: new Abstract: Visual localization is a core technology for augmented reality and autonomous navigation. Recent methods combine the efficient rendering of 3D Gaussian

safetyarxiv-cs-cv

7 May 2026

Tutorials

Understanding In-Context Learning for Nonlinear Regression with Transformers: Attention as Featurizer

arXiv:2605.05176v1 Announce Type: new Abstract: Pre-trained transformers are able to learn from examples provided as part of the prompt without any weight updates, a remarkable ability known as in-con

tutorialsarxiv-cs-lg

UniVer: A Unified Perspective for Multi-step and Multi-draft Speculative Decoding

arXiv:2605.04543v1 Announce Type: new Abstract: Speculative decoding accelerates Large Language Models via draft-then-verify, where verification can be framed as an Optimal Transport (OT) problem. Exi

local-aiarxiv-cs-cl

Tutorials

Unsat Core Prediction through Polarity-Aware Representation Learning over Clause-Literal Hypergraphs

arXiv:2605.04819v1 Announce Type: new Abstract: Graph neural networks have been widely used in Boolean satisfiability (SAT) tasks to learn structural information from SAT formulas. The goal of these s

tutorialsarxiv-cs-lg

v0.30.0-rc4: ci: windows mlx tuning

Based on the release notes available, v0.30.0-rc4 appears to be a release candidate focused on continuous integration and platform-specific optimizations. The title suggests this build targeted Window

local-aiollama-releases

Validity-Calibrated Reasoning Distillation

arXiv:2605.04078v1 Announce Type: new Abstract: Reasoning distillation aims to transfer multi-step reasoning capabilities from large language models to smaller, more efficient ones. While recent metho

local-aiarxiv-cs-lg

Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models

arXiv:2601.21851v2 Announce Type: replace Abstract: Foundation models, despite their robust zero-shot capabilities, remain vulnerable to spurious correlations and 'Clever Hans' strategies. Existing mi

VTAgent: Agentic Keyframe Anchoring for Evidence-Aware Video TextVQA

arXiv:2605.04870v1 Announce Type: new Abstract: Video text-based visual question answering (Video TextVQA) aims to answer questions by reasoning over visual textual content appearing in videos. Despit

Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging

arXiv:2605.05161v1 Announce Type: new Abstract: Zero-shot anomaly localisation via vision-language models (VLMs) offers a compelling approach for rare pathology detection, yet its performance is funda

What Can Be Recovered Under Sparse Adversarial Corruption? Assumption-Free Theory for Linear Measurements

arXiv:2510.24215v4 Announce Type: replace-cross Abstract: Recovery from linear measurements under sparse adversarial corruption is typically formulated as an exact-recovery problem: one seeks structur

Agents

What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity

arXiv:2605.03782v1 Announce Type: new Abstract: To navigate partially observable visual environments, recent VLM agents increasingly internalize world modeling capabilities into their policies via exp

agentsarxiv-cs-ai

Hardware

When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI

arXiv:2605.03213v1 Announce Type: cross Abstract: Agentic AI systems, specifically LLM-driven agents that plan, invoke tools, maintain persistent memory, and delegate tasks to peer agents via protocol

hardwarearxiv-cs-ai

When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data

arXiv:2605.04930v1 Announce Type: new Abstract: Despite theoretical advantages, causal methods for Gene Regulatory Network (GRN) inference from single-cell RNA-seq data consistently fail to match or o

Applications

When LLMs get significantly worse: A statistical approach to detect model degradations

arXiv:2602.10144v2 Announce Type: replace-cross Abstract: Minimizing the inference cost and latency of foundation models has become a crucial area of research. Optimization approaches include theoreti

applicationsarxiv-cs-lg

12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation

model-releasesarxiv-cs-ai

arXiv:2605.01986v1 Announce Type: new Abstract: What if the twelve jurors of Sidney Lumet's 12 Angry Men (1957) were not men, but large language models? Would the one juror who disagrees still be able

6G Needs Agents: Toward Agentic AI-Native Networks for Autonomous Intelligence

model-releasesarxiv-cs-ai

arXiv:2605.01546v1 Announce Type: cross Abstract: Sixth-generation (6G) networks are increasingly envisioned as AI-native infrastructures integrating communication, sensing, and computing into a unifi

A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion

arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl

Agents

A Low-Latency Fraud Detection Layer for Detecting Adversarial Interaction Patterns in LLM-Powered Agents

arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the

agentsarxiv-cs-ai

A Partition-Based Generating Function for Row-Convex Polyominoes

arXiv:2605.03203v1 Announce Type: cross Abstract: An alternative generating function is proposed to enumerate row-convex polyominoes without internal holes on a discrete grid. The approach is based on

researcharxiv-cs-cv

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

A Target-Free Harmonization Method for MRI

arXiv:2605.01282v1 Announce Type: cross Abstract: In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsist

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models

arXiv:2605.00968v1 Announce Type: cross Abstract: Positional encoding plays a pivotal role in determin?ing the extrapolation and generalization performance of wireless foundation models for channel st

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

arXiv:2605.03495v1 Announce Type: new Abstract: We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a

Adaptive Negative Scheduling for Graph Contrastive Learning

model-releasesarxiv-cs-lg

arXiv:2605.03076v1 Announce Type: new Abstract: Graph contrastive learning (GCL) has become a central paradigm for self-supervised representation learning in computational intelligence, with applicati

AHPA: Adaptive Hierarchical Prior Alignment for Diffusion Transformers

arXiv:2605.03317v1 Announce Type: new Abstract: Representation alignment has recently emerged as an effective paradigm for accelerating Diffusion Transformer training. Despite their success, existing

local-aiarxiv-cs-cv

Algebraic Semantics of Governed Execution: Monoidal Categories, Effect Algebras, and Coterminous Boundaries

arXiv:2605.01032v2 Announce Type: new Abstract: We present an algebraic semantics for governed execution in which governance is axiomatized, compositional, and coterminous with expressibility. The fra

Aligning Inductive Bias for Data-Efficient Generalization in State Space Models

arXiv:2509.20789v4 Announce Type: replace Abstract: The remarkable success of modern AI has been closely tied to scaling laws, yet the finite supply of high-quality data makes data efficiency--learnin

safetyarxiv-cs-lg

Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification

model-releasesarxiv-cs-lg

arXiv:2605.03710v1 Announce Type: cross Abstract: Bayesian predictive inference propagates parameter uncertainty to quantities of interest through the posterior-predictive distribution. In practice, t

AMSnet-q: Unsupervised Circuit Identification and Performance Labeling for AMS Circuits

arXiv:2605.01404v1 Announce Type: cross Abstract: Analog and mixed-signal (AMS) circuit design remains heavily reliant on expert knowledge. While recent AI-driven automation tools can generate candida

An Empirical Study of Agent Skills for Healthcare: Practice, Gaps, and Governance

arXiv:2605.02709v1 Announce Type: new Abstract: Healthcare automation is shaped by local procedures and organizational constraints, so agent capabilities rarely transfer unchanged across settings. Age

local-aiarxiv-cs-ai

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music

arXiv:2605.03395v1 Announce Type: cross Abstract: Music popularity prediction has attracted growing research interest, with relevance to artists, platforms, and recommendation systems. However, the ex

Artificial Jagged Intelligence as Uneven Optimization Energy Allocation Capability Concentration, Redistribution, and Optimization Governance

model-releasesarxiv-cs-ai

arXiv:2605.01420v1 Announce Type: new Abstract: Artificial Jagged Intelligence (AJI) denotes a recurring pattern in which large learning systems exhibit strong local capabilities while remaining weak

AsymK-Talker: Real-Time and Long-Horizon Talking Head Generation via Asymmetric Kernel Distillation

arXiv:2605.02948v1 Announce Type: new Abstract: Recent advances in diffusion models have markedly enhanced the visual fidelity of audio-driven talking head generation. Nevertheless, existing methods a

Audio-Visual Intelligence in Large Foundation Models

arXiv:2605.04045v1 Announce Type: new Abstract: Audio-Visual Intelligence (AVI) has emerged as a central frontier in artificial intelligence, bridging auditory and visual modalities to enable machines

safetyarxiv-cs-cv

Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks

arXiv:2605.03759v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs) offer powerful capabilities, they pose privacy risks by unintentionally memorizing sensitive personal informa

Benchmarking Document Parsers on Mathematical Formula Extraction from PDFs

arXiv:2512.09874v2 Announce Type: replace Abstract: Correctly parsing mathematical formulas from PDFs is critical for training large language models and building scientific knowledge bases from academ

BFORE: Butterfly-Firefly Optimized Retinex Enhancement for Low-Light Image Quality Improvement

arXiv:2605.03509v1 Announce Type: new Abstract: Low-light image enhancement is a fundamental challenge in computer vision and multimedia applications, as images captured under insufficient illuminatio

BiMind: A Dual-Head Reasoning Model with Attention-Geometry Adapter for Incorrect Information Detection

arXiv:2604.06022v2 Announce Type: replace Abstract: Incorrect information poses significant challenges by disrupting content veracity and integrity, yet most detection approaches struggle to jointly b

researcharxiv-cs-cl

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

arXiv:2605.03148v1 Announce Type: new Abstract: Reliable wildfire spread prediction is vital for risk-aware emergency planning, yet most deep learning models lack principled uncertainty quantification

researcharxiv-cs-cv

Bridging the Embodiment Gap: Disentangled Cross-Embodiment Video Editing

model-releasesarxiv-cs-ro

arXiv:2605.03637v1 Announce Type: new Abstract: Learning robotic manipulation from human videos is a promising solution to the data bottleneck in robotics, but the distribution shift between humans an

Calibration of the underlying surface parameters for urban flood using latent variables and adjoint equation

model-releasesarxiv-cs-lg

arXiv:2605.02959v1 Announce Type: new Abstract: Calibrating the urban underlying surface parameters is crucial for urban flood simulation. We formulate the parameter calibration problem into an optimi

Can Semantic Methods Enhance Team Sports Tactics? A Methodology for Football with Broader Applications

arXiv:2601.00421v2 Announce Type: replace Abstract: This paper explores how semantic-space reasoning, traditionally used in computational linguistics, can be extended to tactical decision-making in te

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems

arXiv:2605.01758v1 Announce Type: new Abstract: Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulne

Tutorials

Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding

arXiv:2512.17817v3 Announce Type: replace Abstract: While 3DGS has emerged as a high-fidelity scene representation, encoding rich, general-purpose features directly from its primitives remains under-e

tutorialsarxiv-cs-cv

Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents

arXiv:2604.06132v2 Announce Type: replace Abstract: Large language models are increasingly deployed as autonomous agents for multi-step workflows in real-world software environments. However, existing

Code World Model Preparedness Report

arXiv:2605.00932v1 Announce Type: cross Abstract: This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conduc

Agents

Complexity Horizons of Compressed Models in Analog Circuit Analysis

arXiv:2605.02285v1 Announce Type: new Abstract: The deployment of Large Language Models (LLMs) for specialized engineering domains, such as circuit analysis, often faces a trade-off between reasoning

agentsarxiv-cs-ai