Search: “governance”

C-LoRA: Continual Low-Rank Adaptation for Pre-trained Visual Models

arXiv:2502.17920v2 Announce Type: replace Abstract: Pre-trained visual models have become fundamental in computer vision, but they face challenges in continual learning scenarios where data and tasks

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Applications

Cited but Not Consulted: A Counterfactual Audit of Legal Chain-of-Thought Faithfulness

DGX agent

arXiv:2610.12361v1 Announce Type: new Abstract: Large language models increasingly justify legal decisions by naming the statute or precedent behind a verdict, treated as evidence that the decision fo

applicationsarxiv-cs-ai

9 Oct 2026

Cova-PINN: Cross-Domain Conservation Physics-Informed Neural Network for Fluid-Solid Conjugate Heat Transfer in Complex Geometries

arXiv:2610.11108v1 Announce Type: new Abstract: Multi-domain physics-informed neural networks (PINNs) flexibly model medium-specific representations to solve fluid--solid conjugate heat transfer (CHT)

DigitalOcean MicroVMs: Fast, isolated compute for your AI agent infrastructure

Coding-agent platforms, sandbox products, and code-execution services all need the same thing: isolated machines that start up fast, retain their state between bursts of work, and don’t consume comput

agentsdigitalocean

EvoSim: Learning to Model, Modeling to Learn

arXiv:2610.11344v1 Announce Type: new Abstract: Physics-based models connect scientific explanation with quantitative prediction. Constructing them requires selecting physical processes, defining stat

agentsarxiv-cs-ai

Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis

arXiv:2610.11025v1 Announce Type: cross Abstract: Exploratory data analysis (EDA) is rarely open-ended in practice: analysts work from high-level domain questions toward the concrete analyses that can

researcharxiv-cs-ai

Last Week in AI #346 - 719 math manuscripts, 2 Western open models, 1 more safety resignation

model-releaseslast-week-in-ai

OpenAI released 719 mathematics manuscripts on October 6, 2026 that were generated by an internal frontier model (not publicly available), covering 372 topic families—including a solution to the Navie

Learning infinite context windows in recurrent architectures via spatial neural computing

arXiv:2610.10690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-

NOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM Agents

arXiv:2610.11030v1 Announce Type: cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per ac

One Permutation Is All You Need: Fast, Deterministic Feature Importance and Model Stress-Testing

arXiv:2512.13892v3 Announce Type: replace-cross Abstract: Reliable estimation of feature contributions in machine learning models is essential for transparency, algorithmic fairness, and regulatory co

safetyarxiv-cs-ai

PRAXIS: Learning Dynamics of Self-Improving Models with Symbolic Archives

arXiv:2610.11803v1 Announce Type: new Abstract: Self-improving learning systems adapt data selection, optimization, and auxiliary symbolic components, inducing nonstationary objectives outside standar

Predictive Multiplicity in Cell-Fate Assignment: Label-Free Rashomon Sets and the Limits of Per-Cell Certification

arXiv:2610.11185v1 Announce Type: new Abstract: Single-cell trajectory inference maps transcriptomic measurements onto developmental continua, yet configurations that fit the data equally well can ass

Reconstruction of Multiscale Plasma Dynamics Across Operating Regimes

arXiv:2610.11004v1 Announce Type: cross Abstract: Reconstructing spatially resolved plasma dynamics from few sensors is essential for diagnostics, reduced-order modelling and control, yet remains diff

Residual spectral instabilities in representation learning

arXiv:2610.11257v1 Announce Type: new Abstract: Learned representations can lose latent degrees of freedom successively, suggesting a cascade of transitions whose underlying stability principle remain

Verdict Without the Rule: Diagnosing and Auditing Regulatory Rule Sensitivity in LLM Compliance Systems

arXiv:2610.12313v1 Announce Type: new Abstract: Large language model compliance systems are deployed on the assumption that a verdict depends on the regulatory rule it is given. We test this directly

safetyarxiv-cs-ai

WAM-Cache: Staleness-Bounded KV Reuse for Efficient World Action Models

arXiv:2610.11401v1 Announce Type: cross Abstract: World Action Models (WAMs) enable generalist robot manipulation by conditioning an action expert on representations from a pretrained video Diffusion

safetyarxiv-cs-cv

Tutorials

Whose Ground Truth? Embracing Ambiguity in Human-Centered AI

arXiv:2610.10805v1 Announce Type: new Abstract: As AI systems increasingly interact with people and make decisions about them, understanding human interpretations becomes an important part of developi

tutorialsarxiv-cs-ai

A Deafening Silence: Catastrophic Forgetting Lives in the Output Embeddings of Tokens the Data Never Speaks

model-releasesarxiv-cs-cl

arXiv:2610.09835v1 Announce Type: new Abstract: Continual pre-training and fine-tuning in Large Language Models (LLMs) inevitably induce catastrophic forgetting, typically mitigated by replay using of

Boundary-aware Reinforcement Learning for Hypercube State Spaces via Deterministic Policy Gradient

arXiv:2610.09712v1 Announce Type: cross Abstract: We develop a continuous-time deterministic policy gradient framework for reinforcement learning with reflected state dynamics, where the state process

safetyarxiv-cs-lg

Industry

BREAKING: President Trump on Elon Musk today: “First, we honor an industrial titan, a brilliant engineer, and one of the greatest technology…

BREAKING: President Trump on Elon Musk today: “First, we honor an industrial titan, a brilliant engineer, and one of the greatest technology founders to ever live. His name is Elon Musk. Quite honestl

industryelon-musk--x

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existi

safetyarxiv-cs-cl

Do Generative Priors Align with Human Naturalness Perception?

arXiv:2610.09928v1 Announce Type: new Abstract: Visual generative models are trained to capture the probability distributions of natural images, yet whether their native priors reflect the regularitie

safetyarxiv-cs-cv

Google Public Sector and SUNY launch AI-enabled platform to accelerate university research

model-releasesgoogle-cloud-ai

Public research universities solve some of society’s most urgent challenges, but turning ideas into breakthroughs requires fast, secure access to cutting edge technology. In the agentic AI era institu

Tutorials

HealthcareNLP: where are we and what is next?

arXiv:2512.08617v2 Announce Type: replace Abstract: This tutorial focused on Healthcare Domain Applications of NLP, what we have achieved around HealthcareNLP, and the challenges that lie ahead for th

tutorialsarxiv-cs-cl

Online Resource Allocation with an Endogenous Markov State: Fewer LP Solves Earn More

arXiv:2610.09577v1 Announce Type: new Abstract: We study finite-horizon online resource allocation with i.i.d. requests and an endogenous Markov state on a finite state space: each action affects the

Local Ai

OrBIT: Structure-Guided Embedding Compression

arXiv:2610.10385v1 Announce Type: new Abstract: Embedding tables are among the largest components of modern language models. Most compression methods fix a coding geometry such as coordinate blocks, l

local-aiarxiv-cs-lg

Oscillatory Neural Dynamics over Sheaves

arXiv:2610.10018v1 Announce Type: new Abstract: Effective long-range propagation remains a central challenge in graph neural networks, as increasing a model's propagation depth does not guarantee that

Physics-Aligned Electronic Ground-State Learning Improves Generalization

arXiv:2610.10298v1 Announce Type: new Abstract: Machine-learned interatomic potentials (MLIPs) excel at in-distribution tasks, accelerating drug and material development, yet they struggle to generali

Hardware

PoreML: A Data-Driven Framework for Learning Multiphase Flow in Porous Media

arXiv:2610.10314v1 Announce Type: new Abstract: Multiphase flow in porous microstructures is central to CO_2 storage, fuel-cell operation, and flip-chip packaging. Predicting these flows remains chall

hardwarearxiv-cs-lg

Pretraining Shapes Spectral Structure: Architecture- and Strategy-Conditional Prediction of OOD Robustness in Foundation Models

arXiv:2610.09709v1 Announce Type: new Abstract: Can we determine whether a foundation model will generalize out-of-distribution (OOD) before any target data is available? Existing diagnostics require

Running an LLM-driven town with 800+ persistent agents: concurrency, context caching, and inference costs

model-releasesr-localllama

I spent the past year independently building Slow Vale, an LLM-driven life simulation. The Chinese server now has 800+ AI residents sharing one continuously running city. This is an engineering write-

Stability and Diversity of Networked Self-Consuming Generative Ecosystems

arXiv:2610.09409v1 Announce Type: new Abstract: The widespread deployment of generative AI has made it increasingly difficult to distinguish synthetic content from real data. Consequently, synthetic d

StoryBlender: Inter-Shot Consistent and Editable 3D Storyboard with Spatial-temporal Dynamics

arXiv:2604.03315v2 Announce Type: replace Abstract: Storyboarding is a core skill in visual storytelling for film, animation, and games. However, automating this process requires a system to achieve t

researcharxiv-cs-cv

AgentMemGate: Addressing Speculation Contamination in Conversational Assistant Memory

arXiv:2610.07707v1 Announce Type: new Abstract: Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations. A stated plan can ent

Auditable Claims about AI Agents

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

safetyarxiv-cs-ai

CACHEFORGE: LLM-Guided End-to-End Generative Cache Replacement Policy for Performance and Hardware Efficiency

arXiv:2610.07668v1 Announce Type: cross Abstract: Modern cache replacement designs saturate because they operate within fixed representational structures, hand-crafted and heuristic based feature-engi

Local Ai

CausalBind: Causal Modeling and Learning for Protein-Molecule Virtual Screening

arXiv:2610.07340v1 Announce Type: cross Abstract: Protein-molecule virtual screening is increasingly cast as a problem of representation learning in a shared embedding space. Existing methods rely on

local-aiarxiv-cs-ai

Distribution-Transfer Safe-Horizon MPC under Mode Uncertainty

arXiv:2610.07277v1 Announce Type: new Abstract: Scenario-based MPC is an attractive strategy for chance-constrained motion planning that approximates uncertainty via a finite set of sampled scenarios.

researcharxiv-cs-ro

DSV-Mem: Evaluating Multimodal Memory in Professional Workflows for MLLM Agents

arXiv:2610.08102v1 Announce Type: new Abstract: Conversational MLLM agents are increasingly expected to assist in professional workflows, from AI research and engineering design to product management

Humanoid Horizon: Extending Task Horizon in Whole-Body Loco-Manipulation via Parallel Training, Dynamic Starting, and Reward Gating

model-releasesarxiv-cs-ro

arXiv:2610.08320v1 Announce Type: new Abstract: Cluttered indoor environments, where large and heavy objects are scattered across diverse surfaces, require humanoid robots to sequentially navigate, gr

Language-model ratings of depression reflect the rater more than the patient

arXiv:2610.08501v1 Announce Type: cross Abstract: Depression has no diagnostic blood test. Language models promise tireless, consistent assessment, but can accurate raters disagree about individuals?

researcharxiv-cs-ai

Later Is Better: Token Reduction for ViTs Under Distribution Shift

arXiv:2610.07758v1 Announce Type: cross Abstract: Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at

Learned Adaptive Multiresolution Diffusion Imaging

arXiv:2610.07884v1 Announce Type: cross Abstract: Adaptive multiresolution methods reduce representation cost by concentrating fine-scale degrees of freedom where needed, but their tree updates are us

Learning from Revision Consequences: Hindsight Meta-Experience Distillation for Self-Improving Agents

arXiv:2610.07979v1 Announce Type: new Abstract: As agents continuously improve by generating and revising Skills, the process that discovers and refines those Skills becomes a learnable object in its

agentsarxiv-cs-ai

Local Ai

LFHE: Local-First Heuristic Evolution for Bounded Local Topology Search in Decentralized Learning with Non-IID Data

arXiv:2610.08176v1 Announce Type: new Abstract: Decentralized learning is highly sensitive to communication topology under non-IID data. Adaptive peer-selection methods can exploit local model informa

local-aiarxiv-cs-ai

One Step at a Time: Trading LLM Autonomy for Process Predictability

arXiv:2610.07817v1 Announce Type: cross Abstract: Organizations automating operational processes need more than a correct outcome: they need to predict how a process will run, know which one actually

agentsarxiv-cs-ai

Scen-Opt: A Scenario Optimization Toolbox for Data-Driven Convex Programming

arXiv:2610.07846v1 Announce Type: cross Abstract: The scenario approach is a well-established statistical framework for data-driven decision-making. In particular, in data-driven optimization, the sce

Applications

Uniform Discrete Diffusion Models are Minimax Optimal for Estimating Distributions with Small Effective Support Size

arXiv:2610.07655v1 Announce Type: cross Abstract: Discrete diffusion models have emerged as a practically successful framework for generative modeling on discrete product spaces, yet their statistical

applicationsarxiv-cs-lg