Search: “governance”

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

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Safety

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

DGX agent

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

safetyarxiv-cs-ai

2 Oct 2026

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

model-releasesarxiv-cs-lg

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

🚨Potentially huge deal: @SpeakerMenin has introduced NYC legislation that would OBLIGATE third party validation of AI models. Self-policing…

🚨Potentially huge deal: @SpeakerMenin has introduced NYC legislation that would OBLIGATE third party validation of AI models. Self-policing is not enough. Thrilled to see NYC stepping in where the fed

safetygary-marcus--x

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

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

VTV-FM: Flow Matching through Variational Terminal-Velocity Closure

arXiv:2610.00785v1 Announce Type: new Abstract: Flow matching (FM) learns generative transport by fitting continuous-time motion from a simple source distribution to the data distribution. Most existi

researcharxiv-cs-cv

When Harnesses Lose the Signal: Causal Evaluation of Recovery in LLM Agents

arXiv:2610.00372v1 Announce Type: new Abstract: Large language model agents rely on external harnesses to pass information between the model and its environment and to recover from execution errors. Y

Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients

arXiv:2601.23135v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a key driver of language model reasoning. Among RL algorithms, Group Relative Policy Optimization (GRPO) is t

safetyarxiv-cs-lg

ANI: Adaptive Numerical Injection for Unifying Semantic and Arithmetic Representations in Numerical Reasoning

arXiv:2609.39294v1 Announce Type: new Abstract: Precise numerical reasoning with Large Language Models (LLMs) is essential for expanding their applicability to complex real-world tasks. However, text-

applicationsarxiv-cs-ai

Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations

arXiv:2609.38486v1 Announce Type: cross Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomeno

applicationsarxiv-cs-cl

Tutorials

Blackboard Intelligence Can Surpass Autoregressive on Globally Constrained Problems

arXiv:2609.38806v1 Announce Type: cross Abstract: Next-token prediction has driven remarkable progress in large language models, yet a growing body of evidence suggests that they can struggle on probl

tutorialsarxiv-cs-cl

Delta-K: Boosting Multi-Instance Generation via Cross-Attention Augmentation

arXiv:2603.10210v2 Announce Type: replace-cross Abstract: While Diffusion Models excel in text-to-image synthesis, they frequently suffer from catastrophic concept omission when generating complex mul

Divide and Collapse: MAPF-Collapse via Exact Decomposition into Independent Sub-Instances

arXiv:2609.39559v1 Announce Type: new Abstract: In this work we study the problem of MAPFC, a post-optimization step for Multi-Agent Path Finding (MAPF) plans where we are given a feasible plan produc

agentsarxiv-cs-ai

Efficient Active Auditing of Multi-Group Fairness with Bias Probes

arXiv:2609.40034v1 Announce Type: cross Abstract: Over the past decade, Machine Learning (ML) has been trained under dual objectives: minimizing prediction error via Empirical Risk Minimization (ERM)

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning,

Exabeam’s Nova AI agent becomes a persistent investigator as LogRhythm gets AI updates

Behavior intelligence company Exabeam Inc. today introduced a batch of new artificial intelligence features that push its cloud-based New-Scale platform further into agent-driven investigations. The c

agentssiliconangle

Flow Matching under Noisy Latent Structure: Beyond Exact Low-Dimensional Support

arXiv:2609.38918v1 Announce Type: new Abstract: Flow Matching (FM) learns a velocity field whose ODE transports a simple source distribution to a target law. Existing finite-sample theory largely trea

From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye

arXiv:2609.40064v1 Announce Type: new Abstract: Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across co

applicationsarxiv-cs-cl

Grokking through the Lens of Minimum-Norm Interpolation

arXiv:2609.38453v1 Announce Type: new Abstract: Grokking shows that fitting the training data and learning the underlying signal can occur at very different stages. However, existing theories offer li

safetyarxiv-cs-lg

How Does Local Landscape Geometry Evolve in Language Model Pre-Training?

arXiv:2609.39767v1 Announce Type: cross Abstract: The scale and expense of pre-training language models make efficient hyperparameter tuning essential, yet a principled guidance is still missing. In t

local-aiarxiv-cs-ai

How Much Can Reliability Drift Under a Fixed Confidence Distribution?

arXiv:2609.38917v1 Announce Type: new Abstract: A classifier's conditional accuracy can change while its confidence distribution stays exactly the same. We study the worst-case movement of the reliabi

Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

Learning from Research: Toward Lifelong Agent Harness Evolution

arXiv:2609.40169v1 Announce Type: new Abstract: Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve

Let the Carrier Carry the Attack: Preserving the Subject in Adversarial Image Generation

arXiv:2609.39723v1 Announce Type: cross Abstract: Strong unrestricted adversarial attacks can distort the primary object of an image, hereafter referred to as the subject. To preserve subject integrit

researcharxiv-cs-ai

NarrativeSteward: Coordinating Delegation, Guidance, and Verification in Agent-Assisted Interactive Narrative Authoring

arXiv:2609.39333v1 Announce Type: cross Abstract: Autonomous AI agents can turn authors' goals into interactive narratives by independently organizing and carrying out generation and revision. As agen

agentsarxiv-cs-ai

Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning

model-releasesarxiv-cs-lg

arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor

On the Complexity of Preference-Based Bandits

arXiv:2609.39351v1 Announce Type: new Abstract: We study preference-based bandits with general reward function classes, where a learner sequentially selects pairs of arms and observes binary preferenc

researcharxiv-cs-ai

OpenCollab: A Multi-Agent Coding Framework with Programmable Collaboration and Controllable Runtime

arXiv:2609.38345v1 Announce Type: cross Abstract: Multi-agent coding systems are designed to tackle complex software engineering tasks through collaboration. However, existing evaluations typically as

Outsourcing AI regulation to a voluntary 'pledge' conceived by Mark Zuckerberg and endorsed by tech CEOs over a private White House lunch is…

Outsourcing AI regulation to a voluntary 'pledge' conceived by Mark Zuckerberg and endorsed by tech CEOs over a private White House lunch is a recipe for disaster. 'Self-regulation' by tech giants is

safetygary-marcus--x

Passive Stiffness Shaping in Cable-Suspended Aerial Manipulation via Movable Compliant Anchors

arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica

local-aiarxiv-cs-ro

Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model

arXiv:2609.40358v1 Announce Type: new Abstract: Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical

agentsarxiv-cs-cv

Scale and Selection: What Makes Automatic Harness Evolution Work for Visual-Interface Robot Agents

arXiv:2609.39304v1 Announce Type: cross Abstract: When an off-the-shelf coding agent is used directly as a robot policy, observing a browser-based 3D interface through screenshots and acting by posing

Hardware

Shared Phase and Retention Control for Efficient Adaptive Spectral Recurrence

arXiv:2609.39082v1 Announce Type: new Abstract: As new evidence arrives, a sequence model must update what it remembers and how memory influences predictions. While Transformers incur computation and

hardwarearxiv-cs-lg

The future of browser-based security: Leveraging browser data for proactive defense

The browser has changed significantly. Rather than just a window to the web, it serves as an AI workspace and central operating environment for the modern enterprise. With knowledge workers spending o

agentsgoogle-cloud-ai

VERA: Verifiable Feasibility Representations with Counterfactual Credit for Constrained Multi-Agent Control

arXiv:2609.38889v1 Announce Type: new Abstract: Constrained multi-agent control requires more than predicting rewarding actions: an action can cease to be executable as contact windows, shared capacit

safetyarxiv-cs-lg