Search: “governance”

RegenHarness: A Robot Agent Harness with Evidence-Gated Recursive Self-Improvement

arXiv:2609.27612v1 Announce Type: new Abstract: Long-horizon robot execution requires a clear distinction between a model's proposal, a controller's termination, and verified task completion. We prese

agentsarxiv-cs-ro

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Repairability of Inexact Solvers in Recursive State Estimation with Machine Learning

DGX agent

arXiv:2609.28425v1 Announce Type: cross Abstract: Recursive state estimation often executes approximate numerical solutions inside a feedback loop, where highly accurate local steps do not guarantee b

local-aiarxiv-cs-lg

24 Sept 2026

Robustness of Diffusion Models under Distribution Shift

arXiv:2609.27546v1 Announce Type: cross Abstract: Score-based diffusion models are increasingly considered in settings where the underlying data distribution may differ from the training distribution,

Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer

arXiv:2609.28372v1 Announce Type: cross Abstract: Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using 'Tool-Lab,' an adaptation of

agentsarxiv-cs-ai

Theoretical Study on the Evidential Learning-based Variational Autoencoder

arXiv:2609.27853v1 Announce Type: cross Abstract: A normal--inverse-gamma (NIG) latent hierarchy has four parameters, but its induced latent law does not identify all four. For sigma^2simInvGamma(alph

Variational Bayesian Flow Network for Graph Generation

arXiv:2601.22524v2 Announce Type: replace Abstract: Graph generation aims to sample discrete node and edge attributes while satisfying coupled structural constraints. Diffusion models for graphs often

VMMU: A Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark

arXiv:2508.13680v5 Announce Type: replace Abstract: We introduce VMMU, a Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark designed to evaluate how vision-language models (VLMs) in

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2609.27603v1 Announce Type: cross Abstract: In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: t

A Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approach

arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level t

local-aiarxiv-cs-ai

AIGC Video Detection based on the fusion of spatial-frequency-optical flow multimodal features

arXiv:2609.26274v1 Announce Type: new Abstract: The rapid evolution of generative AI (e.g., Sora, Hunyuan) makes it essential to develop effective detection strategies that can generalize across ever-

safetyarxiv-cs-cv

Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Making

arXiv:2609.24644v1 Announce Type: cross Abstract: As people turn to generative AI for financial advice, these systems can personalize how they communicate and what they say. Whether these forms of per

researcharxiv-cs-ai

Beyond Predictable Paths: Redefining AI Security Incident Reporting for Agents

arXiv:2609.24515v1 Announce Type: cross Abstract: AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting become

agentsarxiv-cs-ai

Building Trustworthy Mental Health Benchmarks on Bluesky: A Validation-Aware Weak-Supervision Framework

model-releasesarxiv-cs-ai

arXiv:2609.22696v1 Announce Type: new Abstract: Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, l

CompKV: Compensation-Aware KV Selection for Long-Context LLM Inference

arXiv:2609.26300v1 Announce Type: new Abstract: Despite their strong performance, large language models (LLMs) are bottlenecked by KV cache memory traffic during long-context inference. Sparse attenti

Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech

arXiv:2609.24016v1 Announce Type: new Abstract: Commercial large language models are increasingly deployed across African fintech infrastructure for fraud detection and customer communication, yet no

Few-Shot Demonstrations Elicit the Use of In-Context World Representations in LLMs

arXiv:2609.24352v1 Announce Type: new Abstract: Large language models (LLMs), when acting as agents, are expected to take observed data in context, infer the latent state space underlying the world, a

agentsarxiv-cs-ai

From Research Frontier to Laboratory Bench: Design of a Four-Tier Experimental Teaching System for Multimodal Medical Image Intelligent Diagnosis

arXiv:2609.22790v1 Announce Type: new Abstract: Undergraduate programmes in intelligent medical engineering are expanding, yet laboratory curricula lag behind the multimodal, long-tailed, and distribu

GameDirector: Decoupling Gameplay Logic from Rendering for Player-Configurable Game World Models

arXiv:2609.25652v1 Announce Type: new Abstract: Recent game world models support realistic visual simulation and interactive gameplay based on player inputs. However, they typically learn environment

agentsarxiv-cs-cv

Human-guided physics-constrained AI agents construct an auditable model of soil-plug evolution

arXiv:2609.23360v1 Announce Type: cross Abstract: Engineering predictions require physical mechanisms to be translated consistently into equations, discretization, code, and validation, yet errors can

local-aiarxiv-cs-ai

MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution

arXiv:2609.24838v1 Announce Type: new Abstract: Medical agents increasingly combine general reasoning models with specialized clinical tools, yet their capabilities remain largely fixed by what clinic

Neural Approximation by Function Composition: Rigidity and Doubly Exponential Convergence

arXiv:2609.25874v1 Announce Type: new Abstract: Deep neural networks approximate functions by composing affine maps with nonlinear activations, but how composition itself creates approximation power i

Statistical Rates for Entropic Optimal Transport in the Discrete to SubGaussian Regime

arXiv:2609.26647v1 Announce Type: cross Abstract: We study statistical rates in entropic optimal transport in the semi-discrete regime where one measure has finite support and the other is subGaussian

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

arXiv:2604.02279v2 Announce Type: replace Abstract: Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44

Trains but Doesn't Learn: A Post-Training Delivery Benchmark for LLM Agents as Forward-Deployed Engineers

arXiv:2609.25237v1 Announce Type: cross Abstract: Post-training is becoming a service (PTaaS): a customer hands an operator data and a goal, and a forward-deployed engineer (FDE) returns a fine-tuned,

Trustworthy Agentic AI: Failure Modes, Mitigation Strategies, and a Lifecycle Framework for Autonomous LLM Systems

arXiv:2609.22712v1 Announce Type: new Abstract: Agentic AI systems built on large language models can plan over multiple steps, use external tools, retain information in memory, and coordinate with ot

Variational objectives for amortized Bayesian inference in inverse problems: The role of posterior conditioning

arXiv:2609.25145v1 Announce Type: cross Abstract: Variational autoencoders (VAEs) offer an efficient approach to amortized Bayesian inference for inverse problems, but posterior accuracy can depend st

WatchPoint: Executable User Feedback for Real-World Agentic Web Development

arXiv:2609.26204v1 Announce Type: cross Abstract: When a professional web developer's code fails a test, they do not simply re-read the stack trace. They open the application in a browser, click butto

When are bosonic Gaussian states classical to learn?

arXiv:2609.26705v1 Announce Type: cross Abstract: A fundamental question in physics is: When does classical behavior emerge from quantum systems? Bosonic Gaussian states provide a natural setting to e

You Only Need 2/3 of the Chosen Experts: An Empirical Study of Dynamic Expert Pruning in Fine-Grained MoE LLMs

arXiv:2609.25809v1 Announce Type: new Abstract: Fine-grained mixture-of-experts (MoE) architectures have become a mainstream design for open-weight LLMs, with hundreds of experts and increasingly many

A Channel-Boosted Multi-Agent System with Iterative Consultation for Document Sensitivity Classification

arXiv:2609.22212v1 Announce Type: new Abstract: Organizations in critical national infrastructure sectors must assess heterogeneous documents for sensitivity before routing or storage. Manual assessme

A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents

arXiv:2601.12538v2 Announce Type: replace-cross Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) de

agentsarxiv-cs-cl

Algebraic Consistency Alone Does Not Certify Temporal Structure in Latent Action Models

arXiv:2609.23478v1 Announce Type: new Abstract: Latent action models infer a code for the transition between two frames of action-free video. Recent methods regularise this code to compose additively

researcharxiv-cs-cv

AniPrO: Interpretable Anime Image Provenance Detection via Multi-Dimensional Semantic Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.23345v1 Announce Type: new Abstract: As generative AI becomes increasingly used in anime-style image creation, distinguishing human-drawn, AI-inpainted, and text-to-image images is importan

Tutorials

Blind Thermodynamic Ontology Discovery from Anonymous Experiments

arXiv:2609.23387v1 Announce Type: new Abstract: Before a machine learning model can learn a thermodynamic equation of state, it must discover what its measurements represent: which channels scale with

tutorialsarxiv-cs-lg

Calibrated Decisions at Scale: Converting Police Crash Narratives into Probabilistic Crash Variables with a System One Model (Jev)

arXiv:2609.24052v1 Announce Type: new Abstract: Crash datasets that carry an investigator narrative hold information the coded fields omit. Coding those narratives at scale has been blocked by three o

researcharxiv-cs-cl

Applications

Deep Persona: A Psychologically Grounded Architecture and Evaluation Framework for Role-Playing Agents and Simulations

arXiv:2609.22255v1 Announce Type: new Abstract: Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character descriptions that fail to sustain coherent

applicationsarxiv-cs-cl

Exactness at Inference: A Representational Criterion for Out-of-Distribution Generalization

arXiv:2609.24942v1 Announce Type: new Abstract: A model generalizes outside its training distribution only when it computes a representation structurally equivalent to the generating mechanism, not an

Jev-Mem: System-One-Controlled Agentic Memory for Efficient AI Agents

arXiv:2609.23986v1 Announce Type: cross Abstract: Agentic memory is becoming essential for long-horizon AI agents, yet many existing systems rely on autoregressive LLMs to control how memories are org

agentsarxiv-cs-lg

Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

arXiv:2609.24882v1 Announce Type: new Abstract: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from hig

local-aiarxiv-cs-lg

Measuring the Assistant's Harmlessness Preferences on the User Turn

arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays

local-aiarxiv-cs-cl

MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions

arXiv:2609.24547v1 Announce Type: new Abstract: Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive,

safetyarxiv-cs-ro

On the Information-Theoretic Limits of Latent-Space Watermarking Through Pretrained Generators

arXiv:2609.24377v1 Announce Type: cross Abstract: We study latent-space watermarking through a pretrained generator using a prescribed latent-to-output stochastic mapping, called the renderer. A water

ORDER: A Fictitious-World Benchmark for Domain-Adaptive Embodied AI

model-releasesarxiv-cs-ro

arXiv:2609.22285v1 Announce Type: new Abstract: Adapting language models to new domains via continual pre-training raises a basic evaluation problem: if the training corpus overlaps with what the mode

Personalized Federated Reinforcement Learning via Model-Agnostic Meta-Learning: Convergence of Exact and Hessian-Free Meta-Policy Gradients

arXiv:2609.22833v1 Announce Type: new Abstract: We study personalized federated reinforcement learning, in which n agents, each acting in its own Markov decision process, collaborate through a server

safetyarxiv-cs-lg

PRISM-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Tobacco Product and Legislative Policy Reasoning

arXiv:2609.23769v1 Announce Type: new Abstract: The disambiguation of semantically similar statutory text across jurisdictions is a retrieval problem that existing methods do not solve. This inter-con

safetyarxiv-cs-cv

Propose, Verify, Commit: Evidence-Grounded Memory for Long-Horizon Multi-Actor Conversations

arXiv:2609.23465v1 Announce Type: new Abstract: Long-horizon conversational memory is especially challenging in multi-actor settings, where relevant evidence is distributed across participants and con

Provably Efficient Reinforcement Learning in Continuous-Time Episodic MDPs with Poisson Decision Epochs

arXiv:2609.23127v1 Announce Type: new Abstract: Many real-world reinforcement learning (RL) problems evolve in continuous time, where decisions occur at irregular, event-driven intervals rather than a

local-aiarxiv-cs-lg

Selective Commitment for Language-Guided Object Retrieval under Partial Observability

arXiv:2609.23131v1 Announce Type: new Abstract: Language-guided object retrieval under partial observability requires deciding whether to gather more evidence, interact with the scene, grasp a candida

safetyarxiv-cs-ro