Search: “governance”

LLM-BabyBench: Can Language Models Plan in Worlds They Can Simulate?

model-releasesarxiv-cs-cl

arXiv:2505.12135v2 Announce Type: replace-cross Abstract: When an interactive benchmark reports a single success rate for a language-model agent, it is rarely clear what that number measures. A failur

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ORQA: An Occupation-Realistic Question and Answer Framework for LLM Professional Knowledge

DGX agent

arXiv:2609.12366v1 Announce Type: new Abstract: We present ORQA, a method for testing occupation-level knowledge in large language models. Prior methods either map abstract LLM skills to occupations v

model-releasesarxiv-cs-cl

14 Sept 2026

PACEvolve: Enabling Progress-Aware Consistent Evolution

arXiv:2601.10657v3 Announce Type: replace-cross Abstract: Self-evolving agents powered by Large Language Models (LLMs) have emerged as a promising direction across diverse domains, including code opti

safetyarxiv-cs-lg

Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning

arXiv:2502.07250v3 Announce Type: replace Abstract: Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many

Self-supervised Pre-training Helps Retinal Disease Progression Modelling Most When Data Is Scarce

arXiv:2609.12834v1 Announce Type: new Abstract: Modelling how a disease progresses over time requires longitudinal imaging cohorts, which are scarce and small, whereas cross-sectional data -- one imag

researcharxiv-cs-cv

Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders

arXiv:2505.13569v3 Announce Type: replace Abstract: The use of machine learning for modeling, understanding, and controlling large-scale physics systems is quickly gaining in popularity, with examples

SWARM: A Multilingual Human-Annotated Dataset for Russian Propaganda Detection in Search Engine Results

model-releasesarxiv-cs-cl

arXiv:2609.12653v1 Announce Type: new Abstract: Russian state propaganda spreads across many languages and online spaces. Yet, most computational work examines only one such space, usually social medi

Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems

arXiv:2603.07357v3 Announce Type: replace Abstract: Latent generative models have emerged as powerful priors for solving inverse problems. These models typically represent a class of natural signals a

Agents

Autonomous Chemical Mechanistic Discovery through Agentic Reasoning and Validation

arXiv:2609.11147v1 Announce Type: new Abstract: Unraveling reaction mechanisms is central to modern chemistry, yet automating these investigations remains challenging because computational workflows s

agentsarxiv-cs-ai

12 Sept 2026

Demystifying the Privacy-Utility Trade-off in LLM Interactions

arXiv:2609.10992v1 Announce Type: new Abstract: The integration of Large Language Models into daily tasks relies on context-rich instructions, inevitably exposing sensitive user information. Current p

local-aiarxiv-cs-ai

12 Sept 2026

Verification of Adaptive Agentic Controllers through Finite Rule Revision

arXiv:2607.09770v2 Announce Type: replace Abstract: Industrial agentic AI systems increasingly exhibit a gap between prototype capability and production deployment. In particular, adaptive agents may

12 Sept 2026

A distribution-free certification framework for trustworthy crash-severity prediction

arXiv:2609.11592v1 Announce Type: cross Abstract: Crash-severity models inform screening, dispatch and site prioritization, yet are deployed without a finite-sample statement of what one prediction me

A Function-Space Approach to the Statistical Mechanics of Learning Dynamics

arXiv:2609.09589v1 Announce Type: new Abstract: Deep neural networks exhibit regular macroscopic behavior despite highly nonlinear dynamics in vast parameter spaces. We develop a statistical-mechanica

Agents

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

arXiv:2609.09647v1 Announce Type: new Abstract: Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding th

agentsarxiv-cs-ai

Equity Promotion in Online Resource Allocation

arXiv:2112.04169v3 Announce Type: replace-cross Abstract: We consider online resource allocation under a typical non-profit setting, where limited or even scarce resources are administered by a not-fo

researcharxiv-cs-ai

INDRA: A New AI Tool for Exploring Tobacco, Fossil Fuel, and Chemical Industry Archives

arXiv:2609.11261v1 Announce Type: cross Abstract: Five decades of litigation have disgorged hundreds of millions of pages of formerly secret business records from the tobacco industry, along with docu

safetyarxiv-cs-cl

OpenDiscoveryTrace: Process Traces for Evaluating AI Scientist Workflows

arXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs---generated code, hypotheses, or papers---yet discard the reasoning process

Optimizing AI Inference Across the Deployment Stack

arXiv:2609.10550v1 Announce Type: cross Abstract: AI deployment performance is shaped not by model architecture alone, but by interactions among compression, compiler transformations, and serving poli

Agents

ORCH: Organizational Principles Enable Collective Intelligence in Embodied AI

arXiv:2609.11737v1 Announce Type: cross Abstract: Collective intelligence depends not only on the capabilities of individual members, but also on how those members are organized. Yet artificial multi-

agentsarxiv-cs-lg

Polyhedral Geometry of Time-to-First-Spike Neural Networks

arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv

Prevalence Determines Precision:Silent Contamination in Detector-Defined Datasets

arXiv:2609.11449v1 Announce Type: new Abstract: Many ML datasets are constructed by running a detector, heuristic, or model over candidate pools; accepted items become labels. Dataset precision is the

Tutorials

Rethinking Handwritten Character Recognition

arXiv:2609.10572v1 Announce Type: new Abstract: Non-Latin handwritten character recognition (HCR) remains understudied. Dominant methods consider it as generic image classification, which uses model s

tutorialsarxiv-cs-cv

Seven Sources of Physical AI Capability Formation

arXiv:2609.09627v1 Announce Type: new Abstract: Capabilities relevant to Physical AI can arise from materially different formation histories, yet existing taxonomies organized by morphology, architect

researcharxiv-cs-ai

Watermarks Without Verification: AI Text Watermarking After the EU AI Act

arXiv:2609.09604v1 Announce Type: cross Abstract: On August 2, 2026, the obligations of Article 50 of the EU AI Act took effect, requiring generative AI providers to mark the content their systems pro

A Data-Driven Framework for Identifying and Prioritizing RPA Opportunities in Healthcare Processes

arXiv:2609.09137v1 Announce Type: new Abstract: Robotic Process Automation (RPA) is widely used to reduce administrative burden in United States hospitals, yet an estimated 30-50% of RPA initiatives u

applicationsarxiv-cs-ai

Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending

arXiv:2609.09945v1 Announce Type: new Abstract: Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where appli

An Explainable Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Using Molecular Descriptors

arXiv:2609.10012v1 Announce Type: new Abstract: Blood-brain barrier (BBB) permeability is a critical determinant in the development of central nervous system therapeutics because it directly influence

An Exponential Deterministic--Randomized Gap in ERM-Oracle Complexity for Thresholds on an Unknown Order

arXiv:2609.10196v1 Announce Type: new Abstract: Attias, Hanneke and Ramaswami (NeurIPS 2025) asked whether randomization provably reduces the oracle calls needed for online learning when the class is

applicationsarxiv-cs-lg

Beyond Right and Wrong: Evaluating Second-order Social Reasoning in Large Language Models

arXiv:2609.05437v1 Announce Type: new Abstract: Previous AI alignment efforts have focused primarily on first-order social norms -- teaching models what is socially acceptable or unacceptable (e.g., `

safetyarxiv-cs-ai

Constraint-Aware Discrete Black-Box Optimization Using Tensor Decomposition

arXiv:2609.09370v1 Announce Type: new Abstract: Discrete black-box optimization is often addressed using approaches such as Sequential Model-Based Optimization (SMBO), which aims to improve sample eff

applicationsarxiv-cs-lg

Copying explains the collective behavior of AI agents in the wild

model-releasesarxiv-cs-cl

arXiv:2609.09150v2 Announce Type: replace-cross Abstract: In June 2026, thousands of AI agents found that a small public wiki would accept edits from inside their sandboxes, and started using it to he

Customer Relationship Intelligence: Integrating CRM and MDM for Enhanced Customer Engagement

arXiv:2609.06189v1 Announce Type: new Abstract: This study examines how Customer Relationship Management (CRM), Master Data Management (MDM), and Customer Knowledge Management (CKM) jointly constitute

applicationsarxiv-cs-ai

Encrypt What Matters: When Selective Homomorphic Inference Is Efficient

arXiv:2609.09357v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) enables inference on private data without revealing it to the server, but evaluating an entire input under FHE is e

local-aiarxiv-cs-lg

EvolveScaler: Synthesizing Information-Evolution Contexts via Executable State Machines and Natural-Language Rendering

arXiv:2609.08435v2 Announce Type: new Abstract: In persistent interactions, long contexts may encode an evolving process rather than a fixed record: later events can revise or revoke earlier informati

researcharxiv-cs-ai

Frame-Coded Legged Locomotion over Noisy Terrain

arXiv:2609.10273v1 Announce Type: cross Abstract: Open-loop multilegged locomotion over rough terrain has been interpreted as matter transport over a noisy channel: leg-ground interactions are discret

local-aiarxiv-cs-ro

From Monolithic Blending to Agentic Orchestration: Dynamic Response for Conversational Assistants at Scale

arXiv:2609.05758v2 Announce Type: new Abstract: Conversational assistants can blend retrieval, action selection, escalation, and wording in a single model path, or separate those roles. We report a pr

safetyarxiv-cs-ai

How (Mis)calibrated is your Federated CLIP and what to do about it?

arXiv:2512.04305v3 Announce Type: replace Abstract: Vision-language models (VLMs) such as CLIP are increasingly adapted across decentralized data silos, yet the reliability of their predictions under

researcharxiv-cs-cv

IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier

arXiv:2609.10494v1 Announce Type: new Abstract: Enterprises deploy systems, not checkpoints. Usable capability depends jointly on weights, serving route, precision, output contract, and harness, yet a

applicationsarxiv-cs-cl

Inductive Biases in Field-Level Cosmological Inference from Galaxy Catalogs

arXiv:2609.09504v1 Announce Type: cross Abstract: We perform field-level likelihood-free inference of the matter density parameter Omega_m from simulated galaxy catalogs using machine learning models

Kernel-Managed Shared Memory for System-Wide Personalization

arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema

Networked Admissibility-Preserving Control for Directed Safe Coordination

arXiv:2609.09384v1 Announce Type: cross Abstract: This paper addresses safety-critical coordination for scalar agents whose distributed commands are implemented through constrained physical-input dyna

safetyarxiv-cs-ro

OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis

arXiv:2609.10364v1 Announce Type: new Abstract: Simultaneous assessment of medical imaging and patient records is often required in clinical diagnosis. However, standard machine learning algorithms ca

local-aiarxiv-cs-lg

Hardware

Ordinary, Reasonable Chatbots: Do AI Models Track Human Legal Judgments?

arXiv:2609.06769v1 Announce Type: cross Abstract: As people increasingly rely on artificial intelligence (AI) for guidance in their own lives, scholars, lawyers, and even judges have begun to consider

hardwarearxiv-cs-ai

Privacy-Preserving Split Learning for Federated LLM Fine-Tuning

arXiv:2609.09794v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) on domain-specific data is essential for downstream adaptation. In many deployments, a participant cannot hold

local-aiarxiv-cs-lg

Semigroup-JEPA: Latent Dynamics Consistency for Zero-Shot Physics Generalization

model-releasesarxiv-cs-cv

arXiv:2609.10464v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architecture (JEPA) world models learn a compact latent representation of the world that supports prediction and planning,

The Emergence of Social Science of Large Language Models

arXiv:2509.24877v3 Announce Type: replace Abstract: The social science of large language models (LLMs) examines how these systems evoke mind attributions, interact with one another, and transform huma

safetyarxiv-cs-ai

The Mutations of Machine Speech

arXiv:2609.09496v1 Announce Type: new Abstract: Algorithmic outputs now populate the digital environments through which contemporary life is organized. The role of law in facilitating and constituting

applicationsarxiv-cs-cl

A Systematic Analysis of Automatic Differentiation versus Discretization-based Constraints for Physics-Informed PDE Solvers

arXiv:2609.07437v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) represent a growing frontier in using artificial intelligence to solve partial differential equations (PDEs).