Search: “governance”

Dialogue based Interactive Explanations for Safety Decisions in Human Robot Collaboration

arXiv:2604.05896v2 Announce Type: replace Abstract: As robots increasingly operate in shared, safety critical environments, acting safely is no longer sufficient robots must also make their safety dec

safetyarxiv-cs-ro

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Model Releases

ExecTune: Effective Steering of Black-Box LLMs with Guide Models

DGX agent

arXiv:2604.09741v1 Announce Type: cross Abstract: For large language models deployed through black-box APIs, recurring inference costs often exceed one-time training costs. This motivates composed age

model-releasesarxiv-cs-ai

14 Apr 2026

From Perception to Autonomous Computational Modeling: A Multi-Agent Approach

model-releasesarxiv-cs-cl

arXiv:2604.06788v2 Announce Type: replace-cross Abstract: We present a solver-agnostic framework in which coordinated large language model (LLM) agents autonomously execute the complete computational

HearthNet: Edge Multi-Agent Orchestration for Smart Homes

arXiv:2604.09618v1 Announce Type: cross Abstract: Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing

arXiv:2604.10955v1 Announce Type: new Abstract: Hypergraph neural networks (HGNNs) have shown remarkable potential in modeling high-order relationships that naturally arise in many real-world data dom

IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly

arXiv:2604.10409v1 Announce Type: cross Abstract: We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly an

Learning Racket-Ball Bounce Dynamics Across Diverse Rubbers for Robotic Table Tennis

model-releasesarxiv-cs-ro

arXiv:2604.11349v1 Announce Type: new Abstract: Accurate dynamic models for racket-ball bounces are essential for reliable control in robotic table tennis. Existing models typically assume simple line

PRISM Risk Signal Framework: Hierarchy-Based Red Lines for AI Behavioral Risk

arXiv:2604.11070v1 Announce Type: new Abstract: Current approaches to AI safety define red lines at the case level: specific prompts, specific outputs, specific harms. This paper argues that red lines

Pyramid MoA: A Probabilistic Framework for Cost-Optimized Anytime Inference

arXiv:2602.19509v3 Announce Type: replace-cross Abstract: We observe that LLM cascading and routing implicitly solves an anytime computation problem -- a class of algorithms, well-studied in classical

Reasoning as Data: Representation-Computation Unity and Its Implementation in a Domain-Algebraic Inference Engine

arXiv:2604.10908v1 Announce Type: new Abstract: Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(A

Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party Framework

arXiv:2603.14968v2 Announce Type: replace-cross Abstract: While watermarking serves as a critical mechanism for LLM provenance, existing secret-key schemes tightly couple detection with injection, req

safetyarxiv-cs-cl

RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation

arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr

SpectralLoRA: Is Low-Frequency Structure Sufficient for LoRA Adaptation? A Spectral Analysis of Weight Updates

arXiv:2604.10649v1 Announce Type: cross Abstract: We present a systematic empirical study of the spectral structure of LoRA weight updates. Through 2D Discrete Cosine Transform (DCT) analysis of train

researcharxiv-cs-cl

Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network

arXiv:2604.11479v1 Announce Type: new Abstract: As global political tensions rise and the anticipation of additional tariffs from the United States on international trade increases, the issues of econ

Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes

arXiv:2604.10371v1 Announce Type: new Abstract: This study proposes Structural Gating and Effect-aligned Discovery for Temporal Causal Discovery (SGED-TCD), a novel and general framework for lag-resol

SymphoMotion: Joint Control of Camera Motion and Object Dynamics for Coherent Video Generation

arXiv:2604.03723v2 Announce Type: replace Abstract: Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle o

The Geometry of Knowing: From Possibilistic Ignorance to Probabilistic Certainty -- A Measure-Theoretic Framework for Epistemic Convergence

arXiv:2604.09614v1 Announce Type: new Abstract: This paper develops a measure-theoretic framework establishing when and how a possibilistic representation of incomplete knowledge contracts into a prob

Variance-Aware Prior-Based Tree Policies for Monte Carlo Tree Search

arXiv:2512.21648v2 Announce Type: replace-cross Abstract: Monte Carlo Tree Search (MCTS) has profoundly influenced reinforcement learning (RL) by integrating planning and learning in tasks requiring l

Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis

arXiv:2604.10800v1 Announce Type: cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified concl

agentsarxiv-cs-ai

Adaptive Simulation Experiment for LLM Policy Optimization

arXiv:2604.08779v1 Announce Type: new Abstract: Large language models (LLMs) have significant potential to improve operational efficiency in operations management. Deploying these models requires spec

AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments

arXiv:2604.06111v2 Announce Type: replace Abstract: Existing Agent benchmarks suffer from two critical limitations: high environment interaction overhead (up to 41% of total evaluation time) and imbal

From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales

arXiv:2604.08591v1 Announce Type: cross Abstract: Hallucinations in large ASR models present a critical safety risk. In this work, we propose the extit{Spectral Sensitivity Theorem}, which predicts a

How Similar Are Grokipedia and Wikipedia? A Multi-Dimensional Textual and Structural Comparison

arXiv:2510.26899v5 Announce Type: replace-cross Abstract: The launch of Grokipedia, an AI-generated encyclopedia developed by Elon Musk's xAI, was presented as a response to perceived ideological and

PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics

arXiv:2604.09058v1 Announce Type: cross Abstract: Long-horizon spatiotemporal prediction remains a challenging problem due to cumulative errors, noise amplification, and the lack of physical consisten

PilotBench: A Benchmark for General Aviation Agents with Safety Constraints

arXiv:2604.08987v1 Announce Type: new Abstract: As Large Language Models (LLMs) advance toward embodied AI agents operating in physical environments, a fundamental question emerges: can models trained

Precise Shield: Explaining and Aligning VLLM Safety via Neuron-Level Guidance

arXiv:2604.08881v1 Announce Type: new Abstract: In real-world deployments, Vision-Language Large Models (VLLMs) face critical challenges from multilingual and multimodal composite attacks: harmful ima

Self-Sovereign Agent

arXiv:2604.08551v1 Announce Type: cross Abstract: We investigate the emerging prospect of self-sovereign agents -- AI systems that can economically sustain and extend their own operation without human

agentsarxiv-cs-lg

TopoFlow: Topography-aware Pollutant Flow Learning for High-Resolution Air Quality Prediction

arXiv:2602.16821v2 Announce Type: replace Abstract: We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality predictio

researcharxiv-cs-lg

Traj2Action: A Co-Denoising Framework for Trajectory-Guided Human-to-Robot Skill Transfer

arXiv:2510.00491v3 Announce Type: replace-cross Abstract: Learning diverse manipulation skills for real-world robots is severely bottlenecked by the reliance on costly and hard-to-scale teleoperated d

A Benchmark of Classical and Deep Learning Models for Agricultural Commodity Price Forecasting on A Novel Bangladeshi Market Price Dataset

arXiv:2604.06227v1 Announce Type: new Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developi

AE-ViT: Stable Long-Horizon Parametric Partial Differential Equations Modeling

arXiv:2604.06475v1 Announce Type: new Abstract: Deep Learning Reduced Order Models (ROMs) are becoming increasingly popular as surrogate models for parametric partial differential equations (PDEs) due

An Agentic Evaluation Architecture for Historical Bias Detection in Educational Textbooks

arXiv:2604.07883v1 Announce Type: cross Abstract: History textbooks often contain implicit biases, nationalist framing, and selective omissions that are difficult to audit at scale. We propose an agen

safetyarxiv-cs-cl

Are Stochastic Multi-objective Bandits Harder than Single-objective Bandits?

arXiv:2604.07096v1 Announce Type: new Abstract: Multi-objective bandits have attracted increasing attention because of their broad applicability and mathematical elegance, where the reward of each arm

Assessing the Added Value of Onboard Earth Observation Processing with the IRIDE HEO Service Segment

arXiv:2604.07120v1 Announce Type: cross Abstract: Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Informatio

agentsarxiv-cs-ai

Asymptotic-Preserving Neural Networks for Viscoelastic Parameter Identification in Multiscale Blood Flow Modeling

arXiv:2604.06287v1 Announce Type: new Abstract: Mathematical models and numerical simulations offer a non-invasive way to explore cardiovascular phenomena, providing access to quantities that cannot b

Formalizing building-up constructions of self-dual codes through isotropic lines in Lean

arXiv:2604.08485v1 Announce Type: cross Abstract: The purpose of this paper is two-fold. First we show that Kim's building-up construction of binary self-dual codes is equivalent to Chinburg-Zhang's H

researcharxiv-cs-cl

Information as Structural Alignment: A Dynamical Theory of Continual Learning

arXiv:2604.07108v1 Announce Type: cross Abstract: Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existi

Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks

arXiv:2604.06255v1 Announce Type: cross Abstract: Stellar astrophysics relies critically on accurate descriptions of the physical conditions inside stars. Traditional solvers such as exttt{MESA} (Mo

Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

arXiv:2604.08425v1 Announce Type: cross Abstract: When humans label subjective content, they disagree, and that disagreement is not noise. It reflects genuine differences in perspective shaped by anno

safetyarxiv-cs-cl

LUMINA: Foundation Models for Topology Transferable ACOPF

arXiv:2603.04300v2 Announce Type: replace Abstract: Foundation models in general promise to accelerate scientific computation by learning reusable representations across problem instances, yet constra

MO-RiskVAE: A Multi-Omics Variational Autoencoder for Survival Risk Modeling in Multiple MyelomaMO-RiskVAE

arXiv:2604.06267v1 Announce Type: cross Abstract: Multimodal variational autoencoders (VAEs) have emerged as a powerful framework for survival risk modeling in multiple myeloma by integrating heteroge

OrgForge: A Multi-Agent Simulation Framework for Verifiable Synthetic Corporate Corpora

arXiv:2603.14997v2 Announce Type: replace Abstract: Building and evaluating enterprise AI systems requires synthetic organizational corpora that are internally consistent, temporally structured, and c

agentsarxiv-cs-cl

ParseBench: A Document Parsing Benchmark for AI Agents

arXiv:2604.08538v1 Announce Type: new Abstract: AI agents are changing the requirements for document parsing. What matters is semantic correctness: parsed output must preserve the structure and

Applications

Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics

arXiv:2604.08503v1 Announce Type: new Abstract: Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However

applicationsarxiv-cs-cv

Revisiting Fairness Impossibility with Endogenous Behavior

arXiv:2604.06378v1 Announce Type: cross Abstract: In many real-world settings, institutions can and do adjust the consequences attached to algorithmic classification decisions, such as the size of fin

See the Forest for the Trees: Loosely Speculative Decoding via Visual-Semantic Guidance for Efficient Inference of Video LLMs

arXiv:2604.05650v2 Announce Type: replace Abstract: Video Large Language Models (Video-LLMs) excel in video understanding but suffer from high inference latency during autoregressive generation. Specu

researcharxiv-cs-cl

Spectral Edge Dynamics Reveal Functional Modes of Learning

arXiv:2604.06256v1 Announce Type: cross Abstract: Training dynamics during grokking concentrate along a small number of dominant update directions -- the spectral edge -- which reliably distinguishes

Hardware

Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets

arXiv:2604.07177v1 Announce Type: cross Abstract: We investigate the feasibility of real-time 3D Gaussian Splatting (3DGS) rasterisation on edge clients with varying Gaussian splat counts and GPU comp

hardwarearxiv-cs-lg