Search: “governance”

SafeLand: Safe Autonomous Landing in Unknown Environments with Bayesian Semantic Mapping

arXiv:2603.17430v2 Announce Type: replace Abstract: Autonomous landing of uncrewed aerial vehicles (UAVs) in unknown, dynamic environments poses significant safety challenges, particularly near people

safetyarxiv-cs-ro

6 Aug 2026

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Model Releases

SciCode-Verified: How Benchmark Defects Underestimated the Scientific-Coding Ability of Language Models

DGX agent

arXiv:2608.04975v1 Announce Type: cross Abstract: SciCode is the standard measure of the scientific-coding ability of language models: research-level problems that demand both frontier scientific theo

model-releasesarxiv-cs-ai

6 Aug 2026

Toward Federated Large Language Models in Medicine: A Parameter-Efficient Framework for Privacy-Preserving, Multi-Institutional Adaptation

model-releasesarxiv-cs-cl

arXiv:2601.22124v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because pr

6 Aug 2026

AI Alignment and Fiduciary Obligation

arXiv:2608.02660v1 Announce Type: cross Abstract: Advanced AI assistants engage users in extended interactions across a widening range of roles, including advice, decision support, collaboration, lear

safetyarxiv-cs-ai

Deep Divide-and-Reduce in Symbolic Regression

arXiv:2608.02628v1 Announce Type: cross Abstract: Symbolic regression (SR) is the task of discovering underlying patterns from data and representing them using mathematical expressions. Current machin

researcharxiv-cs-ai

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability

arXiv:2511.19716v3 Announce Type: replace-cross Abstract: Stochastic Gradient Descent (SGD) often slows in the late stage of training due to anisotropic curvature and gradient noise. We analyze precon

Local Ai

DiagLoop: A Counterfactual Data Flywheel with Stage-Localized Reinforcement for Diagnostic LLMs

arXiv:2608.03674v1 Announce Type: new Abstract: Causal diagnostic models must explain how conclusions follow from evidence because diagnoses guide repairs and treatments. Yet serious cases are scarce,

local-aiarxiv-cs-lg

DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers

arXiv:2608.03082v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled remarkable progress in visual synthesis, benefiting from their superior scalability. To fa

Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization

arXiv:2608.03045v1 Announce Type: new Abstract: We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black

Formal Verification of Agentic Systems over Operational Data

arXiv:2608.03609v1 Announce Type: new Abstract: Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data.

agentsarxiv-cs-ai

Knowing the Form, Not the Function: Automatically Auditing Answer--Authority Decoupling in Legal Benchmarks

arXiv:2608.02621v1 Announce Type: cross Abstract: Legal benchmarks typically score final answers even when models also state legal authority. We test whether answer correctness can serve as a proxy fo

On the Diversity of Analogy Making in Large Language Models

arXiv:2608.03233v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity.

OR-Agent: Bridging Evolutionary Search and Structured Research for Automated Algorithm Discovery

arXiv:2602.13769v3 Announce Type: replace Abstract: Automating heuristic design in complex, experiment-driven domains requires more than iterative mutation of solution algorithms. Current LLM-based ev

agentsarxiv-cs-ai

StreamDAM: Presence-Aware Memory for Real-Time Streaming Video Object Segmentation

arXiv:2608.03912v1 Announce Type: new Abstract: Quality-tier video object segmentation (VOS) trackers such as DAM4SAM top accuracy leaderboards, but they are measured offline, one frame at a time with

Studying, Identifying, and Fixing Hidden Technical Debt in AI-Intensive Cyber-Physical Systems

arXiv:2608.02638v1 Announce Type: cross Abstract: Artificial Intelligence (AI) components are increasingly pervasive in several software systems, including Cyber-Physical Systems (CPSs). AI-CPS are us

agentsarxiv-cs-ai

Taming the Implicit: Dual-Channel Risk-Aware Reinforcement Fine-Tuning for Continual Multimodal Post-Training

arXiv:2608.03660v1 Announce Type: new Abstract: Reinforcement fine-tuning (RFT) is widely believed to inherently resist catastrophic forgetting in continual post-training of multimodal large language

The Signal Horizon: Local Blindness and the Contraction of Pauli-Weight Spectra in Noisy Quantum Encodings

arXiv:2602.14735v2 Announce Type: replace-cross Abstract: The performance of quantum classifiers is typically analyzed through global state distinguishability or the trainability of variational models

safetyarxiv-cs-lg

WeClawArena: An Auditable Sandbox and Benchmark for Cross-User Agents Collaboration and Security in Human-Centered Agent Networks

arXiv:2608.03499v1 Announce Type: new Abstract: Recent advances in persistent personal-agent frameworks are making human-centered agent networks realistic deployment targets: each user can be served b

When Memory Becomes Authority: Benchmarking Authority Collapse at the Memory Consolidation Boundary

arXiv:2608.01679v2 Announce Type: replace Abstract: Persistent memory allows (self-evolving) LLM agents to adapt across tasks by consolidating heterogeneous interaction histories into reusable facts,

Applications

A Robotic System for Automated Manufacturing of Dielectric Elastomer Actuators

arXiv:2608.00369v1 Announce Type: new Abstract: This letter presents an automated robotic manufacturing system for soft capacitors which operate as actuators and sensors. Emphasis is placed on the two

applicationsarxiv-cs-ro

Beyond Illumination: A Conditional Mutual Information-Guided Network for Low-Light Image Enhancement

arXiv:2608.01886v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) seeks to restore structural fidelity, natural color rendition, and proper exposure from images captured under inadequ

researcharxiv-cs-cv

Computational Approaches to Understanding Large Language Model Impact on Writing and Information Ecosystems

arXiv:2506.17467v2 Announce Type: replace Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across soci

Conservation laws determine what physical learning remembers

arXiv:2608.00097v1 Announce Type: cross Abstract: Physical learning rules such as equilibrium propagation (EP), coupled learning (CL), and adjoint coupled learning (AL) train resistive networks throug

DiffuseAgent-MI: Distributionally-Grounded,Tool-Integrated Self-Evolving Agents for Faithful Visual Reasoning

arXiv:2608.00540v1 Announce Type: new Abstract: Tool-integrated vision-language agents have made remarkable progress on compositional and multi-step visual reasoning. Yet their outputs frequently exhi

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View

arXiv:2608.01357v1 Announce Type: new Abstract: Traditional approximation theory measures convergence rates in terms of the number of parameters or degrees of freedom. However, practical computation o

Embodied Passive Aeroacoustic Perception Enables Relative Sensing and Pursuit Between Aerial Robots

arXiv:2608.00401v1 Announce Type: new Abstract: Aerial robots generate structured aeroacoustic fields during flight, yet these signals have been underexplored as a source of onboard relative perceptio

researcharxiv-cs-ro

Tutorials

Exemplars in Disguise: Pure Exemplar Models Mimic Abstraction-First Learning

arXiv:2608.00821v1 Announce Type: new Abstract: Whether idiosyncratic, item-specific knowledge is learned before abstract class-level generalizations, or vice versa, is a central question in language

tutorialsarxiv-cs-cl

Factorized AdaBoost.MH Achieves the Same Convergence Rate as AdaBoost.MH

arXiv:2608.01091v1 Announce Type: new Abstract: AdaBoost.MH reduces multi-class classification to a collection of binary subproblems and enjoys the classical boosting-type convergence guarantee under

Feed-Forward Steering in Transformer Residual Dynamics

arXiv:2608.02071v1 Announce Type: new Abstract: Attention-only dynamical theories model Transformer residual directions as particles aggregating on a sphere. We extend this framework by incorporating

From AI Weather Prediction to Infrastructure Resilience: A Real-Time Correction-Downscaling Framework for Tropical Cyclone Impact Forecasting

arXiv:2603.12828v2 Announce Type: replace-cross Abstract: This paper addresses a missing capability in infrastructure resilience: turning fast, global AI weather forecasts into asset-scale, actionable

safetyarxiv-cs-lg

From Forest to Future Capital: Tracking Land Cover Change in Ibu Kota Nusantara (IKN) from 2021 to 2026 with PlanetScope Imagery

arXiv:2608.01230v1 Announce Type: new Abstract: Indonesia's relocation of its political and administrative capital from Jakarta to Ibu Kota Nusantara (IKN) has been framed around a ``Forest City'' vis

researcharxiv-cs-cv

Identifiability-Aware Source Apportionment in City-Scale Advection-Diffusion Systems

arXiv:2608.00050v1 Announce Type: cross Abstract: Source apportionment from sparse urban air-quality sensors is an inverse problem limited by sensor placement, wind-driven transport, background variat

Intention Inference Under Execution Noise: Separating Aleatoric and Epistemic Uncertainty in Social Dilemmas

arXiv:2608.02440v1 Announce Type: cross Abstract: In noisy social dilemmas, intended actions are stochastically corrupted before execution, so an observed defection may reflect hostile intent or actio

Local Ai

Local Shapley: Model-Induced Locality and Optimal Reuse in Data Valuation

arXiv:2603.03672v2 Announce Type: replace Abstract: The Shapley value provides a principled foundation for data valuation, but exact computation is #P-hard due to the exponential coalition space. Exis

local-aiarxiv-cs-lg

Machine-Precision Prediction of Low-Dimensional Chaotic Systems from Noise-Free Data

arXiv:2507.09652v2 Announce Type: replace-cross Abstract: Low-dimensional chaotic systems such as the Lorenz-63 model are commonly used to benchmark system-agnostic methods for learning dynamics from

Hardware

MiniWorld: Democratizing the Training of Video World Models from Scratch

arXiv:2608.01127v1 Announce Type: new Abstract: Video world models predict future observations conditioned on historical observations and control signals, enabling long-horizon generation through auto

hardwarearxiv-cs-cv

MonitorVLM-v2: A Deployed Vision-Language Framework for Real-Time Safety Violation Detection

arXiv:2608.00975v1 Announce Type: new Abstract: Large vision--language models (VLMs) can reason step by step about complex visual scenes, but this open-ended, autoregressive chain-of-thought (CoT) app

On the Identifiability of Masked Prediction: Mode Blindness and Mask Schedules

arXiv:2608.01383v1 Announce Type: new Abstract: Masked prediction learns representations by fitting a schedule-weighted family of conditional laws, but it remains unclear when near-optimal conditional

Round-Trip Consistency: Bidirectional Diffusion Models Can Predict Their Own Rollout Errors

arXiv:2608.00675v1 Announce Type: cross Abstract: Autoregressive models accumulate error over long rollouts, yet at deployment there is no ground truth to measure it against. We train a single conditi

Trajectories That Segment Themselves: Agent-Declared Boundaries as a Training Unit

arXiv:2608.02302v1 Announce Type: cross Abstract: Long-horizon coding-agent trajectories are poorly matched to the credit units available to train on: a single action has no stable value, an episode l

agentsarxiv-cs-lg

Uncertainty-guided active learning for surrogate prediction of stream-finishing wear fields

arXiv:2608.00593v1 Announce Type: cross Abstract: In stream finishing, the wear experienced by a workpiece depends strongly on its orientation within the rotating abrasive media. Determining suitable

Understanding Sparse Attention Selectivity in Long-Context Foundation Models via Counterfactual Evaluation

arXiv:2608.01676v1 Announce Type: new Abstract: Sparse attention is widely deployed in long-context serving stacks, yet no framework audits how discarding blocks changes the influence of specific cont

Local Ai

Accelerated Random-Sweep Gibbs Sampling for Gaussian Graphical Models via Dual Normal Factor Graphs

arXiv:2607.28706v1 Announce Type: cross Abstract: We study the convergence properties of the random-sweep Gibbs sampler for Gaussian graphical models with a thin-membrane prior. We demonstrate that th

local-aiarxiv-cs-lg

Benchmarks Are Not Validation: A System-Level View of Financial LLM Applications

model-releasesarxiv-cs-cl

arXiv:2607.28840v1 Announce Type: new Abstract: Large language models are increasingly deployed in financial applications that combine retrieval, proprietary data, tool use, orchestration logic, monit

DART: Dual-Axis Airborne Reachability-Gated Torque-Reaction for Off-Road Vehicle Jumps

model-releasesarxiv-cs-ro

arXiv:2607.29011v1 Announce Type: new Abstract: Traversing crests, ledges, and ditches at high speed often launches vehicles into the air, and a mishandled landing presents a substantial crash hazard.

Evidence-Type Competition: When Can Interventional Data Teach Language Models Causal Direction?

arXiv:2607.29484v1 Announce Type: new Abstract: Interventional data is widely regarded as the gold standard for teaching models causal reasoning. We test this assumption in a fully controlled syntheti

Guarantees on Dynamical System Distinguishability for LLM Token Generation

arXiv:2607.28667v1 Announce Type: cross Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a

researcharxiv-cs-ai

HarnessBank: Semantic Gene-Bank Search with Gated Verification for Agent-Harness Self-Evolution

arXiv:2607.13683v2 Announce Type: replace Abstract: Large Language Models (LLMs) have enabled capable agents across diverse applications. Beyond the foundation model, the performance of an agent is go

agentsarxiv-cs-cl