Search: “governance”

SupraTITO: Transferable Generative Molecular Dynamics for Supramolecular Systems

arXiv:2610.01381v1 Announce Type: cross Abstract: Peptide sequence governs both the structures formed through supramolecular assembly and the dynamics by which they emerge, but predicting either requi

2 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Tokenized Key-Gated Adapter Routing: A Secure Access Control Mechanism Against Private Data Leakage in LLMs

DGX agent

arXiv:2610.00309v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in privacy-critical domains (e.g., healthcare, finance, and government), but their propensity t

model-releasesarxiv-cs-ai

2 Oct 2026

A Competing-Hazards Systematization of Loss of Control in Autonomous Agents

arXiv:2609.38411v1 Announce Type: new Abstract: Leading AI developers have reported agents acting beyond their approved limits, which a United Nations panel described as an early warning of loss of hu

Composing Task-specific Agent Harnesses at Test Time with Reusable Primitives

arXiv:2609.38912v1 Announce Type: new Abstract: Agent harnesses govern how large language models (LLMs) gather context, invoke tools, verify results, preserve state, and terminate, largely affecting a

DynaHarness: A Dynamic Physical Harness for Self-Evolving Robot Agents

arXiv:2609.40306v1 Announce Type: cross Abstract: Pretrained robot policies provide useful action priors, but long-horizon manipulation still requires coordination between semantic reasoning and physi

Learning Continuous Neural Representation of Stochastic Hybrid Systems

arXiv:2609.38893v1 Announce Type: cross Abstract: A stochastic hybrid system (SHS) is governed by a stochastic differential equation (SDE) describing the continuous dynamics and a Markov reset kernel

Tutorials

Residuals Are Not Enough: Limits of Physics-Informed Pre-Training for Scientific Foundation Models

arXiv:2503.19081v2 Announce Type: replace Abstract: Scientific foundation models (SciFMs) aim to learn generalizable representations of physical systems governed by partial differential equations (PDE

tutorialsarxiv-cs-lg

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

arXiv:2609.39773v1 Announce Type: new Abstract: Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models a

Beyond Semantics: How Temporal Biases Shape Retrieval in Transformer and State-Space Models

arXiv:2510.22752v2 Announce Type: replace-cross Abstract: In-context learning is governed by both temporal and semantic relationships, shaping how Large Language Models (LLMs) retrieve contextual info

Bits Under ZK-LLM: Evaluating Zero-Knowledge-Friendly Quantization for Verifiable Private LLM Inference

arXiv:2609.36437v1 Announce Type: new Abstract: Zero-knowledge proofs are emerging as a promising approach for enabling private, verifiable LLM governance and auditing, where regulators, users, and au

CI-PINN: Causal Integral Physics-Informed Neural Network for Solving Evolution Equations

arXiv:2609.36615v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) solve partial differential equations (PDEs) by incorporating governing physical laws into the training loss.

Compiling Learning Problems into Adaptation Programs for Language Models

arXiv:2609.37371v1 Announce Type: cross Abstract: Model adaptation is typically governed by a fixed recipe, even though different update programs can produce substantially different behavioral outcome

Identifying ODEs from Unstructured Data with Causal Representation Learning

arXiv:2609.37083v1 Announce Type: cross Abstract: We study the problem of recovering the governing ODE of a dynamical system from unstructured, high-dimensional observations such as images. Existing m

Learning Nonlinear Finite Element Solution Operators using Multilayer Perceptrons and Energy Minimization

arXiv:2412.04596v3 Announce Type: replace Abstract: We develop and evaluate a method for learning solution operators to nonlinear problems governed by partial differential equations (PDEs). The approa

Probabilistic Symbolic-Distillation Model of Droplet Collision for Spray Simulation at High Ambient Pressures

arXiv:2609.37202v1 Announce Type: cross Abstract: Droplet collision governs droplet population dynamics in many chemical engineering processes, such as spray drying, spray cooling, agricultural sprayi

Relic: From Multi-Agent Collaboration to Persistent Organizational Capability

arXiv:2609.32965v2 Announce Type: replace Abstract: Multiple agents may often conflict in an organization: for example, one coding agent changes an interface in a repository, but another continues to

SINO: Scale-Invariant Neural Operator

arXiv:2609.36890v1 Announce Type: new Abstract: In scientific machine learning, physical fields governed by partial differential equations exhibit low-rank structure and scale invariance. When solving

CORTEX: A Verified Experience Layer for Generalist Agents

arXiv:2609.33260v1 Announce Type: cross Abstract: An agent can solve a task today and face the same task under new facts, tools, or governing knowledge tomorrow. Most agent systems can retrieve releva

safetyarxiv-cs-lg

Geometry-Aware Operator Families for Structured Representation Learning

arXiv:2609.33089v1 Announce Type: new Abstract: The geometry of latent representations governs which components should interact and how information should propagate, making geometry-aware operator des

Singularities of Non-negative Matrix Factorization and their application to Bayesian inference

arXiv:2609.34043v1 Announce Type: cross Abstract: Non-negative matrix factorization (NMF) is a singular statistical model whose Bayesian asymptotics are governed by the real log canonical threshold (R

The Composition Gap in Dataset Distillation

arXiv:2609.34343v1 Announce Type: new Abstract: Dataset distillation compresses a training set into a small synthetic set, usually evaluated one at a time. In federated and data-governance settings, s

The limits of exactness: On the failure of automatic differentiation in physics-informed machine learning

arXiv:2609.33078v1 Announce Type: new Abstract: Automatic differentiation (AD) lets neural networks compute derivatives of governing equations to machine precision, and this precision has made it the

A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models

arXiv:2609.30292v1 Announce Type: cross Abstract: Online reviews shape consumer decisions, platform governance, and corporate reputation.Fake reviews compromise this information channel by injecting d

'AI is (not) the new...': A Diagnostic Analogy Framework for Generative AI's Cultural Impacts

arXiv:2609.31482v1 Announce Type: new Abstract: Generative AI is reshaping the cultural infrastructures through which knowledge is found, synthesized, and held accountable. To make sense of this shift

Beyond Approved Actions: Runtime Validation of Persistent Outcomes in Agent Workflows

arXiv:2609.31301v1 Announce Type: cross Abstract: Large language model agents increasingly act on software systems, no longer merely generating text but also changing databases and online services. Ho

FTB Graph: Determining and Validating First-token Broadcasters and Language-Identity Head Circuits in Multilingual Language Models

arXiv:2609.30954v1 Announce Type: new Abstract: Large language models operating in multilingual contexts must resolve target response languages early in generation, yet the causal circuitry governing

Learning coarse-step dynamics and internal mechanical response with graph networks

arXiv:2609.30344v1 Announce Type: new Abstract: Modern sensing records the motion of physical systems, but often leaves the forces and mechanical response governing that motion unobserved. Inferring t

AgentKernel: The Trust-Native Agentic Operating System

arXiv:2609.29647v1 Announce Type: cross Abstract: Modern AI agents routinely cross trust boundaries: they ingest untrusted content, combine it with privileged instructions, persist intermediate belief

Certified Task-Conditioned Active Observability

arXiv:2609.28520v1 Announce Type: cross Abstract: Before acting upon an unobservable physical system, an autonomous agent must determine which latent distinctions govern downstream tasks, how many act

From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO_x Memristive Devices

arXiv:2609.30047v1 Announce Type: cross Abstract: Resistive switching in oxide-based devices is widely governed by stochastic defect processes, yet a predictive link between fabrication conditions and

RD-JEPA: Predictive latent pretraining for few-trajectory transfer across reaction--diffusion equations

arXiv:2609.29403v1 Announce Type: new Abstract: Learning surrogates for time-dependent partial differential equations often requires a new simulation corpus when the governing operator changes. We int

A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization

arXiv:2609.25471v1 Announce Type: new Abstract: Semi-supervised federated learning (SSFL) trains models on clients' unlabeled data using a teacher to generate pseudo-labels, with a small labeled seed

Blaming Across the Aisle: Political Contrasting and Blame Attribution in the Danish Parliament

arXiv:2609.26346v1 Announce Type: new Abstract: Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce. This study examines blame attribution in the Dan

researcharxiv-cs-cl

Local Ai

Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning

arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele

local-aiarxiv-cs-cv

When Agentic Trust Crosses Organizational Boundaries: Structural Externalization and a Reference Model for Trust Evidence

arXiv:2609.22961v1 Announce Type: cross Abstract: Agentic systems increasingly invoke tools, services, data, and other agents across organizational boundaries, yet a relying party cannot assess a dele

Exact Quotients of Fresnel-Kummer Surfaces and Certified Biaxial Refraction

arXiv:2609.23249v1 Announce Type: new Abstract: The Fresnel wave surface governs the propagation of light in a transparent biaxial crystal. It is a special Kummer quartic, and we identify it exactly.

researcharxiv-cs-cv

22 Sept 2026

PhysReflect: Geometry and Perception Guided Diffusion for Physically-Plausible Mirror Reflections

arXiv:2609.23442v1 Announce Type: new Abstract: Diffusion models generate high-quality images, yet often violate the physical laws governing mirror reflections. Reflections often suffer from geometric

safetyarxiv-cs-cv

22 Sept 2026

Predictors and Orchestrators: Parsimonious Machine Learning within an Agentic AI Harness for Multi-Horizon Karst Aquifer Forecasting

arXiv:2609.22251v1 Announce Type: new Abstract: Forecasting karst aquifer dynamics is difficult because recharge responses are nonlinear, event-driven, and governed by strongly heterogeneous flow path

safetyarxiv-cs-lg

22 Sept 2026

CounselReflect: Opportunities and Challenges for Designing Tools to Support Self-Reflection on Mental Health and Well-Being Conversations with AI

arXiv:2603.29429v2 Announce Type: replace Abstract: AI is increasingly used for mental health and well-being support, creating an urgent need for safer engagement, while design, evaluation, and govern

researcharxiv-cs-cl

18 Sept 2026

FairCompressAgent: An Agentic Framework for Fairness-Aware Model Compression for FPGA Deployment

arXiv:2609.17786v1 Announce Type: new Abstract: Fairness-aware model compression requires selecting methods and configurations that balance accuracy, fairness, and deployment cost. These decisions bec

17 Sept 2026

Local Ai

PhysVGGT: Feed-Forward Dense Physical Property Estimation from A Single Image

arXiv:2609.18920v1 Announce Type: new Abstract: Physical properties, such as friction, hardness, stiffness, and density, govern how robots should grasp, manipulate and interact with objects, yet estim

local-aiarxiv-cs-cv

17 Sept 2026

Version- and Scope-Aware Question Answering over Normative Documents: A Deployed System and an End-to-End Evaluation at Production Scale

arXiv:2609.18769v1 Announce Type: new Abstract: Correctly answering a question grounded in normative documents often depends on information outside any single passage: whether the retrieved document i

17 Sept 2026

Applications

Beyond Distribution Matching: Semantics-Consistent Tabular Diffusion with Weak Semantic Priors

arXiv:2609.16069v1 Announce Type: cross Abstract: Synthetic tabular data can match real data distributions while still violating the semantic constraints that govern valid tabular rows. This reveals a

applicationsarxiv-cs-ai

Divergence Timing and Cumulative Disagreement under KV-Cache Eviction

arXiv:2609.16617v1 Announce Type: new Abstract: KV-cache eviction perturbs the conditional token distributions governing autoregressive generation. We investigate how first-divergence timing and subse

Interactive Memory Learning for Long-Term Conversations

arXiv:2609.17088v1 Announce Type: new Abstract: Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these s

Tutorials

Measuring AI harms with multidimensional Lorenz Zonoids

arXiv:2609.16004v1 Announce Type: cross Abstract: While AI systems increasingly shape high-stakes societal domains, their governance is limited by the lack of risk management methods that operate on r

tutorialsarxiv-cs-lg

Measuring Curriculum Alignment across Topical Coverage, Competency, and Cognitive Depth: A Longitudinal Framework Applied to CS2013 and CS2023

arXiv:2606.19469v2 Announce Type: replace Abstract: Undergraduate computer science is governed by international curricular guidelines revised about once a decade, yet programs lack a reliable way to m

An Evolutionary Computation Framework for Multi-Agent Q-Learning with Mean-Field Environmental Feedback

arXiv:2609.13253v1 Announce Type: cross Abstract: Multi-agent reinforcement learning in networked populations is governed by the interaction between individual adaptation, local encounters, and changi