Search: “governance”

Quantifying the Stability of Multi-Step Reasoning via Error Amplification

arXiv:2610.06404v1 Announce Type: new Abstract: We consider the stability of multi-step reasoning processes, which have extensive applications in language models, including chain-of-thought and algori

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Representation--Behavior Alignment for Explainable Weakly-Supervised Video Anomaly Detection

DGX agent

arXiv:2610.05129v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) provide a natural way to make video anomaly detection more explainable. However, their final decisions do not a

model-releasesarxiv-cs-cv

6 Oct 2026

Score Approximation for Diffusion Models on Arbitrary Low-Dimensional Structures

arXiv:2606.19894v2 Announce Type: replace Abstract: Score-based diffusion models have achieved remarkable empirical success, motivating extensive theoretical work to establish their foundations. Howev

applicationsarxiv-cs-lg

Sharp Convergence and Sample Complexity of Policy Mirror Descent for Average-Reward MDPs

arXiv:2610.04117v1 Announce Type: new Abstract: Policy mirror descent (PMD) has a mature finite-time theory in discounted Markov decision processes (MDPs), but less is known in the average-reward sett

safetyarxiv-cs-lg

SoundWeaver: Compositional Warm-Starting for Text-to-Audio Diffusion Serving

arXiv:2603.07865v2 Announce Type: replace-cross Abstract: Text-to-audio (T2A) diffusion models generate high-quality audio but require tens of neural function evaluations (NFEs), resulting in substant

researcharxiv-cs-cv

Terrain-Dependent Intra-Cycle Leg Timing for Effective Locomotion on Granular Slopes

arXiv:2610.04144v1 Announce Type: new Abstract: Locomotion on granular slopes such as sand dunes remains a fundamental challenge for legged robots due to reduced shear strength and gravity-induced ani

researcharxiv-cs-ro

Agents

The Optimization Landscape of Learning Compacted Context Models

arXiv:2610.05885v1 Announce Type: new Abstract: Many works approach continual learning through the lens of infinite context windows. As an agent puts more observation into context (concretely the KV c

agentsarxiv-cs-lg

Weight Decay and Neuron Condensation: A Three-Stage Analysis of Two-Layer ReLU Networks

arXiv:2610.04533v1 Announce Type: new Abstract: Weight decay is widely used as a regularization technique in neural network training, yet its role in neuron condensation (parameter direction alignment

A Two-Stage Cascade for Near-Real-Time Forest Anomaly Detection from Sentinel-1 SAR Time Series

arXiv:2610.02763v1 Announce Type: new Abstract: Tropical forest monitoring is essential for global climate stability and biodiversity preservation. To address the urgent need for rapid, reliable detec

AIBL: Augmented Instance-Based Learning with Structured Memory and Neural Embeddings

arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over

Becoming Suspicious Across Borders: Algorithmic Extraterritoriality and AI-Driven Financial Surveillance

arXiv:2610.03425v1 Announce Type: new Abstract: Suspicion is an important, yet elusive concept in anti-money laundering and counter-terrorist financing (AML/CFT), which allows for intervention below t

applicationsarxiv-cs-ai

Can AI Understand the Language of Origami?

model-releasesarxiv-cs-cv

arXiv:2603.13856v3 Announce Type: replace-cross Abstract: Building AI systems that can plan, act, and create in the physical world requires more than pattern recognition. Such systems must reason abou

Designing the Future of User Feedback for Generative AI

arXiv:2610.02631v1 Announce Type: new Abstract: Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and feature

EVOL: Simulator-Guided Evolutionary Expert Synthesis for Deployment-Free Learning Path Recommendation

arXiv:2610.03273v1 Announce Type: new Abstract: Reinforcement learning (RL) for learning path recommendation (LPR) faces two coupled obstacles. First, the policy must commit to a sequence of L concept

HazardWeaver: Scientific Route Selection for Hazard Analysis Agents

arXiv:2610.03591v1 Announce Type: new Abstract: Understanding and assessing natural hazards is essential for disaster preparedness and risk reduction. Recent advances in large language models have spu

Hyperparameter selection for equation learning with biologically-informed neural networks

arXiv:2610.02954v1 Announce Type: new Abstract: Biologically-informed neural networks (BINNs) have emerged as a flexible subclass of physics-informed neural networks (PINNs) for learning terms in part

Large Language Continuous Diffusion Models

arXiv:2610.02665v1 Announce Type: cross Abstract: Despite the success of discrete diffusion language models (dLMs) for fast parallel decoding, their non-smooth, high-dimensional space hinders trajecto

researcharxiv-cs-ai

Objects Without Morphisms: What LLMs for Mathematics Do Not Represent

arXiv:2610.03551v1 Announce Type: new Abstract: Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them: c

On Unlearning for Time-series Forecasting

arXiv:2610.02865v1 Announce Type: new Abstract: Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, w

Open-Endedness Bench: Measuring Epistemic Process from Agent Records

arXiv:2610.02588v1 Announce Type: new Abstract: Agents are increasingly given open-ended research tasks: discovering an empirical law from self-designed experiments, improving a heuristic whose optimu

Operator-informed initialization for Fourier features physics-informed neural networks

arXiv:2610.03378v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) typically exhibit spectral bias, where some frequencies of the target function converge more slowly than others

safetyarxiv-cs-lg

OptiSelect: How does the Optimizer Shape Data Curriculum?

arXiv:2610.03432v1 Announce Type: cross Abstract: Online data selection has demonstrated substantial efficiency gains for LLM pretraining by training on the most valuable candidates within each batch.

researcharxiv-cs-ai

Positive-Unlabeled Learning for Agent Safety False Alarm Auditing

arXiv:2610.02925v1 Announce Type: new Abstract: Safety monitors help safeguard language-model agents interacting with external tools and environments, but conservative monitoring can generate many fal

Recoverability Has a Law: The ERR Measure for Tool-Augmented Agents

arXiv:2601.22352v2 Announce Type: replace-cross Abstract: Language model agents often appear capable of self-recovery after failing tool call executions, yet this behavior lacks a formal explanation.

SceneFactory-3D: Lifting 2D Traffic Scenes into 3D Physical Counterfactuals for Scalable Physically Grounded Safety Evaluation

arXiv:2610.02874v1 Announce Type: new Abstract: Scalable driving simulators typically execute vehicle commands using prescribed behavioral or kinematic rules, overlooking the physics of tire-road inte

safetyarxiv-cs-ro

SoftGene: Protein Language Model-Enhanced Soft Prompting for Interpretable Gene Set Annotation

arXiv:2610.03029v1 Announce Type: new Abstract: Gene set analysis is a cornerstone of functional genomics, yet it remains labor-intensive and heavily dependent on manual curation and expert biological

Local Ai

Writerslogic at PAN 2026: Process over Content for Robust Detection under Domain Shift

arXiv:2610.03565v1 Announce Type: new Abstract: We describe the Writerslogic systems for three PAN at CLEF 2026 shared tasks (Reasoning Trajectory Detection, Voight-Kampff Generative AI Detection, and

local-aiarxiv-cs-cl

A Comprehensive Review of One-Pixel Attack: Research Status, Taxonomy, Applications, Regulation Policy and Future Directions

arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel ca

safetyarxiv-cs-cv

Agents

A Survey on End-to-End Autonomous Driving Training from the Perspectives of Data, Strategy, and Platform

arXiv:2610.00926v1 Announce Type: cross Abstract: Autonomous driving is a cornerstone technology for the future of intelligent transportation, where end-to-end learning has emerged as a transformative

agentsarxiv-cs-cv

AI Emulation of Stochastic Sudden Stratospheric Warming with Interpretable Latent Structure

arXiv:2610.02069v1 Announce Type: cross Abstract: Rare weather regime transitions pose a challenge for data-driven modeling due to class imbalance. In this study, we develop a probabilistic deep learn

Continual Concept Erasure in Diffusion Models by Suppressing Cross-Edit Interference

arXiv:2610.01989v1 Announce Type: new Abstract: Concept erasure removes copyright-protected, privacy-sensitive, or otherwise undesirable concepts from pretrained text-to-image diffusion models to supp

researcharxiv-cs-cv

Deny Without Disabling: Authorization-Paired Evaluation and Control for Multi-Agent Systems

arXiv:2610.00371v1 Announce Type: cross Abstract: Multi-agent systems derive their capabilities from sharing evidence, delegating tasks, and combining information across agents. The same process creat

ECHO: A Participatory Framework for Bias-Anchored AI Harm Anticipation

arXiv:2512.03068v2 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) systems increasingly shape consequential decisions, creating value but also potential harms for individuals, soci

Local Ai

Enterprise Representation Simplification (ERS): Reducing Representational Complexity for Enterprise AI

arXiv:2610.00791v1 Announce Type: new Abstract: Enterprise information is represented through artifacts shaped by applications, projects, technologies, organizational boundaries, and local requirement

local-aiarxiv-cs-ai

EurekaBench: Measuring Agentic Ability to Discover New Scientific Insights

arXiv:2610.00492v1 Announce Type: cross Abstract: When Isaac Newton discovered the law of gravitation, he did so through an iterative process of analyzing observed data such as planetary patterns, fin

Every Ablation Is a Dose: Counterweights and the Semblance of Self-Repair

arXiv:2610.02173v1 Announce Type: new Abstract: Ablate a component of a language model, and other components often appear to adjust and compensate. This phenomenon, termed self-repair, has been observ

Gradient-Aligned Pair Selection for Personalized Preference Optimization

arXiv:2610.00061v1 Announce Type: new Abstract: Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Dir

In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners

arXiv:2610.01712v1 Announce Type: new Abstract: In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters. While much of the existing the

Initial condition recovery in nonlinear damped viscous photoacoustic tomography using a convolutional neural network-guided gradient-free optimization framework

arXiv:2610.01015v1 Announce Type: cross Abstract: Photoacoustic tomography (PAT) is a hybrid imaging modality that combines high optical contrast with high ultrasonic resolution for biomedical imaging

Machine Translation for Sign Languages

arXiv:2610.00881v1 Announce Type: new Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation s

applicationsarxiv-cs-cv

Moloch's Bargain: Emergent Misalignment When LLMs Compete for Audiences

arXiv:2510.06105v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly shaping how information is created and disseminated, from companies using them to craft persuasive adv

PACE: Provenance-Aware Capability Enforcement for Tool-Using LLM Agents

arXiv:2610.01349v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn generated text into real side effects, so poisoned tool metadata, retrieved pages, memory, and reusa

PhysDEM: Physics-Defined Energy-Matching Diffusion for Spatiotemporal Field Generation under Scarce Measurements

arXiv:2610.01759v1 Announce Type: new Abstract: Generating and predicting spatiotemporal physical fields from scarce measurements is challenging, as observations are insufficient to characterize a dis

applicationsarxiv-cs-cv

Quantifying the Impact of Ambulance Ramping: A Multi-Year Analysis of Victorian Emergency Medical Services Cases

arXiv:2610.00818v1 Announce Type: new Abstract: Ambulance ramping, the delay between hospital arrival and patient handover, is a critical operational bottleneck in Emergency Medical Services (EMS), ye

Roto-translated Local Coordinate Frames For Interacting Dynamical Systems

arXiv:2110.14961v4 Announce Type: replace Abstract: Modelling interactions is critical in learning complex dynamical systems, namely systems of interacting objects with highly non-linear and time-depe

Local Ai

SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL

arXiv:2610.02023v1 Announce Type: new Abstract: While Large Language Models (LLMs) advance 3D indoor scene synthesis, current pipelines fail to retain user-specific preferences across sessions, making

local-aiarxiv-cs-ai

Trustworthy Data- and ML-Ops for Intelligent Transportation Systems and Logistics

arXiv:2610.01282v1 Announce Type: new Abstract: The rapid evolution of Intelligent Transportation Systems and Logistics (ITS&L) has become a cornerstone of the modern social economy, relying heavily o

Understanding Latent Diffusability via Fisher Geometry

arXiv:2604.02751v3 Announce Type: replace Abstract: Diffusion models often degrade in latent spaces, yet the formal causes remain poorly understood. We quantify latent-space diffusability via the rate