All entries

Algorithms with Polynomially-Improved Approximation Factors for the 2 rightarrow q Norm, and Applications

arXiv:2605.25303v1 Announce Type: cross Abstract: The 2 rightarrow q norm of a matrix X in R^{n imes d} is defined as lVert X rVert_{2 rightarrow q} = sup_{lVert v rVert_2 = 1} lVert Xv rVert_q. We gi

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants

DGX agent

arXiv:2605.24742v1 Announce Type: new Abstract: Obtaining consistent explanations for machine learning on molecular graphs requires predictions and attributions to be aligned with chemical identity. H

researcharxiv-cs-lg

26 May 2026

All Leaks Count, Some Count More: Interpretable Temporal Contamination Detection and Mitigation in LLM Backtesting

arXiv:2602.17234v2 Announce Type: replace Abstract: Backtesting LLMs on resolved events assumes models reason only from pre-cutoff knowledge, yet pretrained models inevitably leak post-cutoff knowledg

AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications

arXiv:2602.22769v3 Announce Type: replace Abstract: Large Language Models (LLMs) are deployed as autonomous agents in increasingly complex applications, where enabling long-horizon memory is critical

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting

arXiv:2605.25166v1 Announce Type: cross Abstract: Time series forecasting models are increasingly scaled through large Transformer backbones, yet most existing approaches process all series through a

An Effective-Rank Audit of Alignment-Induced Activation Shifts: Confound Control, Constructive Calibration, and Limits

arXiv:2605.24583v1 Announce Type: cross Abstract: We audit alignment-induced shifts in residual-stream activations of three open-weight instruction-tuned LLMs (Llama-3.1-8B-Instruct, Gemma-2-9B-it, Qw

An Efficient Learning Method to Connect Observables

model-releasesarxiv-cs-lg

arXiv:2503.01684v3 Announce Type: replace-cross Abstract: Constructing fast and accurate surrogate models is a key ingredient for making robust predictions in many topics. We introduce a new model, th

Tutorials

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods

arXiv:2605.24298v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) for automated code generation has enhanced software development efficiency, but often at the cost of s

tutorialsarxiv-cs-ai

An Interactive Paradigm for Deep Research

arXiv:2605.24266v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled deep research systems that synthesize comprehensive, report-style answers to open-ended q

An Interpretable CF-RL-TOPSIS Fusion Model for Skills-Aware Talent Recommendation

arXiv:2605.24155v1 Announce Type: cross Abstract: Effective skills-aware talent recommendation must balance behavioral transition patterns, trajectory-sensitive adaptation, and inspectable occupation-

Analogies between Transformer Layers and Power Method

arXiv:2605.25619v1 Announce Type: new Abstract: In the paper we show that there is an analogy between the operations occurring in a layer of a transformer (projections and layer normalizations, disreg

AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation

arXiv:2601.03191v3 Announce Type: replace-cross Abstract: Multimodal medical large language models have shown substantial progress in chest X-ray interpretation but continue to face challenges in spat

Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation

arXiv:2605.25402v1 Announce Type: cross Abstract: Self-supervised pre-training paradigm has gained increasing prominence for learning transferable representations in medical imaging, yet existing meth

safetyarxiv-cs-ai

ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering

arXiv:2011.10331v4 Announce Type: replace-cross Abstract: Multi-view clustering has wide applications in many image processing scenarios. In these scenarios, original image data often contain missing

Anisotropic Diffusion-Driven Ergodic Coverage in Multi-Robot Systems

arXiv:2605.24125v1 Announce Type: new Abstract: We consider the problem of combining potential field and ergodic search on multi-robot systems. Traditional ergodic search algorithms use metrics for er

agentsarxiv-cs-ro

AnnotateMissense: a genome-wide annotation and benchmarking framework for missense pathogenicity prediction

model-releasesarxiv-cs-lg

arXiv:2605.24520v1 Announce Type: cross Abstract: Missense variant interpretation remains challenging because pathogenicity depends on heterogeneous evidence from population frequency, evolutionary co

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents

arXiv:2605.25971v1 Announce Type: new Abstract: While AI agents demonstrate remarkable capabilities in reasoning and tool use, they remain fundamentally reactive: they compute responses only after exp

AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond

arXiv:2605.26113v1 Announce Type: new Abstract: Generating high-fidelity and controllable synthetic data is critical for advancing end-to-end autonomous driving, particularly for addressing the long t

safetyarxiv-cs-ro

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control

arXiv:2510.20955v2 Announce Type: replace Abstract: Safe decision-making algorithms for control of mobile robots often require the existence of feedback to verify the safety of proposed actions. This

Approximating the universal thermal climate index using sparse regression with orthogonal polynomials

arXiv:2508.11307v3 Announce Type: replace-cross Abstract: The Universal Thermal Climate Index (UTCI) is a measure of thermal comfort that quantifies how humans experience environmental conditions. Due

APT-Agent: Automated Penetration Testing using Large Language Models

arXiv:2605.24949v1 Announce Type: cross Abstract: Penetration testing is essential to securing modern web infrastructures, yet traditional manual methods struggle to keep pace with their scale and com

ARCANE-PedSynth: Synthetic Multi-Pedestrian Datasets with Behavioural Crossing Annotations

arXiv:2605.24950v1 Announce Type: cross Abstract: We present ARCANE-PedSynth, an open-source CARLA-based software framework for generating synthetic multi-pedestrian datasets with dense behavioural an

agentsarxiv-cs-lg

Architecting Agentic Communities using Design Patterns

arXiv:2601.03624v3 Announce Type: replace Abstract: The rapid evolution of Large Language Models (LLM) and subsequent Agentic AI technologies requires systematic architectural guidance for building so

Artificial Effort

arXiv:2605.23920v1 Announce Type: cross Abstract: Real-effort tasks, in which participants perform cognitively costly activities whose outcomes depend on actual performance, are widely used in experim

ArtSplat: Feed-Forward Articulated 3D Gaussian Splatting from Sparse Multi-State Uncalibrated Views

arXiv:2605.24304v1 Announce Type: cross Abstract: Articulated object reconstruction from sparse-view images is an ill-posed problem that requires simultaneous inference of geometry and underlying arti

Asking LLMs to Verify First is Almost Free Lunch

arXiv:2511.21734v2 Announce Type: replace-cross Abstract: To enhance the reasoning capabilities of Large Language Models (LLMs) without high costs of training, nor extensive test-time sampling, we int

Applications

Assessing the Operational Viability of Foundation Models for Time Series Forecasting

arXiv:2605.24381v1 Announce Type: cross Abstract: Time series forecasting drives operational decisions in areas like finance, transportation, and energy. While supervised learning approaches achieve s

applicationsarxiv-cs-ai

Associations between echocardiographic traits and AI-ECG predictions of heart failure

arXiv:2605.24576v1 Announce Type: new Abstract: Artificial intelligence-enabled electrocardiography (AI-ECG) can detect heart failure (HF), including disease not captured by left ventricular ejection

Applications

ASTRO: Adaptive Spatio-Temporal Reinforcement Optimization for GNN Powered Anomly Detection in Cyber Physical Systems

arXiv:2605.25135v1 Announce Type: cross Abstract: Anomaly detection in Industrial Internet of Things (IIoT) environments is essential to protect the Industrial Control Systems (ICS) and Cyber-Physical

applicationsarxiv-cs-ai

AstroMind: A High-Fidelity Benchmark for Spacecraft Behavior Reasoning Based on Large Language Models

arXiv:2605.24573v1 Announce Type: new Abstract: Understanding why a spacecraft maneuvers -- rather than simply that it did -- is an increasingly important problem for space domain awareness as Earth o

Tutorials

Asymmetric Adaptation-based Real-time Fault Diagnosis Under Transitional Operating Conditions

arXiv:2605.24457v1 Announce Type: cross Abstract: Data streams in real-world industrial scenarios often contain transitional operating conditions that are uncovered during offline training, leading to

tutorialsarxiv-cs-lg

Attested Tool-Server Admission: A Security Extension to the Model Context Protocol

arXiv:2605.24248v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) standardizes how a large-language-model (LLM) agent and an external tool server exchange messages, but not trust: a h

ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows

arXiv:2605.25489v1 Announce Type: new Abstract: Visual analytics (VA) workflows are inherently complex, involving data transformation, feature engineering, visual representation, and human interpretat

Auditing medical multi-agent AI reveals risks of false consensus

arXiv:2510.10185v2 Announce Type: replace-cross Abstract: Large language models are increasingly being assembled into medical multi-agent systems that emulate multidisciplinary consultation through sp

safetyarxiv-cs-ai

Aurora Hunter: A Two-Stage Framework for Probabilistic Visibility Forecasting

arXiv:2605.24038v1 Announce Type: cross Abstract: Forecasting aurora borealis visibility matters for space weather research and aurora tourism. Visibility at a site and night depends on two distinct f

Authority Inversion in LLM-Mediated Ubiquitous Systems: When Models Trust Users Over Sensors

arXiv:2605.23938v1 Announce Type: new Abstract: Large language models (LLMs) increasingly fuse heterogeneous inputs in ubiquitous systems. Yet, how LLMs implicitly allocate authority when sensor measu

safetyarxiv-cs-ai

Authority Signals in Claude AI Health Citations: A Descriptive Analysis Using the Authority Signals Framework

arXiv:2605.23921v1 Announce Type: cross Abstract: This study seeks to determine the authority signals used by Anthropic's Claude AI in its presentation of sources when answering consumer health questi

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

Automated Benchmark Auditing for AI Agents and Large Language Models

arXiv:2605.26079v1 Announce Type: new Abstract: Modern AI benchmarks operate at a complexity that outpaces traditional verification methods. Tasks authored by domain experts often contain implicit ass

Automated Detection and Classification of Delusion-related Content in Naturalistic Audio Diaries Using Multi-Agent Language Models

arXiv:2605.24755v1 Announce Type: new Abstract: Speech monologues recorded in naturalistic settings provide opportunities to characterize mental illness phenomenology and detect symptom exacerbation.

Applications

Automated regime classification in multidimensional time series data using sliced Wasserstein k-means clustering

arXiv:2310.01285v2 Announce Type: replace-cross Abstract: Recent work has proposed Wasserstein k-means (Wk-means) clustering as a powerful method to classify regimes in time series data, and one-dimen

applicationsarxiv-cs-lg

Autoregression-Free Neural Operators for Time-Dependent PDEs

arXiv:2605.25413v1 Announce Type: cross Abstract: Neural operators learn mappings from function-dependent inputs to solutions, providing an effective framework for solving partial differential equatio

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction

arXiv:2512.15605v4 Announce Type: replace Abstract: Autoregressive models (ARMs) currently constitute the dominant paradigm for large language models (LLMs). Energy-based models (EBMs) represent anoth

Local Ai

AutoSG: LLM-Driven Solver Generation Solely from Task Prompts for Expensive Optimization

arXiv:2605.25658v1 Announce Type: cross Abstract: Expensive optimization tasks are ubiquitous in real-world applications, demanding highly specialized solvers. While LLM-driven automated solver genera

local-aiarxiv-cs-ai

AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery

arXiv:2604.05550v2 Announce Type: replace Abstract: Artificial intelligence research increasingly depends on prolonged cycles of reproduction, debugging, and iterative refinement to achieve State-Of-T

agentsarxiv-cs-cl

AvalancheBench: Evaluating Enterprise Data Agents Through Latent World Recovery

arXiv:2605.24183v1 Announce Type: cross Abstract: We introduce AvalancheBench, a benchmark for evaluating enterprise data agents through latent world recovery. AvalancheBench improves on existing benc

AvAtar: Learning to Align via Active Optimal Transport

arXiv:2605.24395v1 Announce Type: new Abstract: Alignment plays a fundamental role in many machine learning problems, such as multi-network analysis, multimodal learning, and point cloud registration.

AVBench: Human-Aligned and Automated Evaluation Benchmark for Audio-Video Generative Models

arXiv:2605.24652v1 Announce Type: new Abstract: Rapid advances in audio-video (AV) generation have enabled high-fidelity synthesis with synchronized sound, particularly for human-related scenarios inv