Search: “governance”

VTV-FM: Flow Matching through Variational Terminal-Velocity Closure

arXiv:2610.00785v1 Announce Type: new Abstract: Flow matching (FM) learns generative transport by fitting continuous-time motion from a simple source distribution to the data distribution. Most existi

researcharxiv-cs-cv

2 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

When Harnesses Lose the Signal: Causal Evaluation of Recovery in LLM Agents

DGX agent

arXiv:2610.00372v1 Announce Type: new Abstract: Large language model agents rely on external harnesses to pass information between the model and its environment and to recover from execution errors. Y

safetyarxiv-cs-ai

2 Oct 2026

Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients

arXiv:2601.23135v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a key driver of language model reasoning. Among RL algorithms, Group Relative Policy Optimization (GRPO) is t

safetyarxiv-cs-lg

2 Oct 2026

ANI: Adaptive Numerical Injection for Unifying Semantic and Arithmetic Representations in Numerical Reasoning

arXiv:2609.39294v1 Announce Type: new Abstract: Precise numerical reasoning with Large Language Models (LLMs) is essential for expanding their applicability to complex real-world tasks. However, text-

applicationsarxiv-cs-ai

Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations

arXiv:2609.38486v1 Announce Type: cross Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomeno

applicationsarxiv-cs-cl

Tutorials

Blackboard Intelligence Can Surpass Autoregressive on Globally Constrained Problems

arXiv:2609.38806v1 Announce Type: cross Abstract: Next-token prediction has driven remarkable progress in large language models, yet a growing body of evidence suggests that they can struggle on probl

tutorialsarxiv-cs-cl

Delta-K: Boosting Multi-Instance Generation via Cross-Attention Augmentation

arXiv:2603.10210v2 Announce Type: replace-cross Abstract: While Diffusion Models excel in text-to-image synthesis, they frequently suffer from catastrophic concept omission when generating complex mul

Agents

Divide and Collapse: MAPF-Collapse via Exact Decomposition into Independent Sub-Instances

arXiv:2609.39559v1 Announce Type: new Abstract: In this work we study the problem of MAPFC, a post-optimization step for Multi-Agent Path Finding (MAPF) plans where we are given a feasible plan produc

agentsarxiv-cs-ai

Efficient Active Auditing of Multi-Group Fairness with Bias Probes

arXiv:2609.40034v1 Announce Type: cross Abstract: Over the past decade, Machine Learning (ML) has been trained under dual objectives: minimizing prediction error via Empirical Risk Minimization (ERM)

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning,

Flow Matching under Noisy Latent Structure: Beyond Exact Low-Dimensional Support

arXiv:2609.38918v1 Announce Type: new Abstract: Flow Matching (FM) learns a velocity field whose ODE transports a simple source distribution to a target law. Existing finite-sample theory largely trea

researcharxiv-cs-lg

From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye

arXiv:2609.40064v1 Announce Type: new Abstract: Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across co

applicationsarxiv-cs-cl

Grokking through the Lens of Minimum-Norm Interpolation

arXiv:2609.38453v1 Announce Type: new Abstract: Grokking shows that fitting the training data and learning the underlying signal can occur at very different stages. However, existing theories offer li

safetyarxiv-cs-lg

Local Ai

How Does Local Landscape Geometry Evolve in Language Model Pre-Training?

arXiv:2609.39767v1 Announce Type: cross Abstract: The scale and expense of pre-training language models make efficient hyperparameter tuning essential, yet a principled guidance is still missing. In t

local-aiarxiv-cs-ai

How Much Can Reliability Drift Under a Fixed Confidence Distribution?

arXiv:2609.38917v1 Announce Type: new Abstract: A classifier's conditional accuracy can change while its confidence distribution stays exactly the same. We study the worst-case movement of the reliabi

Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

Learning from Research: Toward Lifelong Agent Harness Evolution

arXiv:2609.40169v1 Announce Type: new Abstract: Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve

Let the Carrier Carry the Attack: Preserving the Subject in Adversarial Image Generation

arXiv:2609.39723v1 Announce Type: cross Abstract: Strong unrestricted adversarial attacks can distort the primary object of an image, hereafter referred to as the subject. To preserve subject integrit

Agents

NarrativeSteward: Coordinating Delegation, Guidance, and Verification in Agent-Assisted Interactive Narrative Authoring

arXiv:2609.39333v1 Announce Type: cross Abstract: Autonomous AI agents can turn authors' goals into interactive narratives by independently organizing and carrying out generation and revision. As agen

agentsarxiv-cs-ai

Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning

arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor

On the Complexity of Preference-Based Bandits

arXiv:2609.39351v1 Announce Type: new Abstract: We study preference-based bandits with general reward function classes, where a learner sequentially selects pairs of arms and observes binary preferenc

OpenCollab: A Multi-Agent Coding Framework with Programmable Collaboration and Controllable Runtime

arXiv:2609.38345v1 Announce Type: cross Abstract: Multi-agent coding systems are designed to tackle complex software engineering tasks through collaboration. However, existing evaluations typically as

Local Ai

Passive Stiffness Shaping in Cable-Suspended Aerial Manipulation via Movable Compliant Anchors

arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica

local-aiarxiv-cs-ro

Agents

Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model

arXiv:2609.40358v1 Announce Type: new Abstract: Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical

agentsarxiv-cs-cv

Scale and Selection: What Makes Automatic Harness Evolution Work for Visual-Interface Robot Agents

arXiv:2609.39304v1 Announce Type: cross Abstract: When an off-the-shelf coding agent is used directly as a robot policy, observing a browser-based 3D interface through screenshots and acting by posing

Hardware

Shared Phase and Retention Control for Efficient Adaptive Spectral Recurrence

arXiv:2609.39082v1 Announce Type: new Abstract: As new evidence arrives, a sequence model must update what it remembers and how memory influences predictions. While Transformers incur computation and

hardwarearxiv-cs-lg

VERA: Verifiable Feasibility Representations with Counterfactual Credit for Constrained Multi-Agent Control

arXiv:2609.38889v1 Announce Type: new Abstract: Constrained multi-agent control requires more than predicting rewarding actions: an action can cease to be executable as contact windows, shared capacit

safetyarxiv-cs-lg

Which Tasks Survive Self-Supervised Learning?

arXiv:2609.38393v1 Announce Type: cross Abstract: Same-instance self-supervised learning (SSL) learns representations by enforcing consistency across two views of the same underlying instance. This pr

A Dual-Track Curation-and-Classification Framework for Resolving Ground-Truth Label Noise in Operational Sentinel-2 Wheat Area Estimation

model-releasesarxiv-cs-cv

arXiv:2609.36975v1 Announce Type: new Abstract: Operational estimation of wheat-cultivated area is persistently constrained by discordance between administrative record-keeping and remotely sensed cla

A theoretical model of dynamical grammatical gender shifting based on set-valued set function

arXiv:2603.03510v3 Announce Type: replace-cross Abstract: This study investigates the diverse characteristics of nouns, focusing on both semantic (e.g., countable/uncountable) and morphosyntactic (e.g

Adversarial Training for Pixel Diffusion

arXiv:2609.38170v1 Announce Type: new Abstract: Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fi

safetyarxiv-cs-cv

ARGOS: Reinforcement Learning-Driven Multidimensional Elasticity for Service Orchestration in the Computing Continuum

arXiv:2609.37085v1 Announce Type: cross Abstract: Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited an

Beyond Interaction Capacity: Estimator Scaling with Recursive Models for CTR Prediction

arXiv:2609.37905v1 Announce Type: cross Abstract: Click-Through Rate prediction, a core task in recommendation and advertising systems, relies on modeling interactions among sparse categorical feature

Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting

arXiv:2609.35795v1 Announce Type: cross Abstract: Asthma deterioration forecasting must remain reli- able when patient populations, sensor ecosystems, and available modalities change across cohorts. E

Can AI Scientists Change Their Minds? Prior-Evidence Conflict in Synthetic Universes

arXiv:2609.36726v1 Announce Type: new Abstract: Can a scientific agent distinguish a law it inferred from evidence from one it merely recognizes? We introduce Synthetic Universes, a controlled benchma

CIRCLE: A Framework for Evaluating AI from a Real-World Lens

arXiv:2602.24055v5 Announce Type: replace Abstract: This study proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI system

applicationsarxiv-cs-ai

Concealing LLM-Based Multi-Agent Topology via Phantom Structure Injection

arXiv:2609.37567v1 Announce Type: cross Abstract: Driven by the rapid advancement of large language models (LLMs), LLM-based multi-agent systems (MAS) have emerged as a powerful paradigm for collabora

Corruption-Robust Sparse Linear Contextual Bandits with Knapsack Constraints

arXiv:2609.37189v1 Announce Type: new Abstract: We study sparse linear contextual bandits with knapsack constraints under joint reward and consumption corruption. Consumption corruption creates a chal

Local Ai

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models

arXiv:2609.35947v1 Announce Type: new Abstract: Many inference-time tasks for pretrained discrete diffusion models and diffusion language models reduce to drawing samples from a tilted version of the

Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps

arXiv:2602.12624v2 Announce Type: replace-cross Abstract: Diffusion-based generative models have achieved remarkable performance across various domains, yet their practical deployment is often limited

researcharxiv-cs-cv

From Sketch Prior to Trajectories: A Mission-Oriented Coordinated Navigation Framework for Indoor UAV Swarm

arXiv:2607.11386v2 Announce Type: replace Abstract: UAV swarm for applications, such as indoor inspection, security patrol, and logistics delivery, are often mission-oriented rather than exploration-o

safetyarxiv-cs-ro

Fundamental Limits of Transferability and Equivariance in Algebraic Signal Models I: Finite Dimensions

arXiv:2609.36106v1 Announce Type: cross Abstract: We study the fundamental limits of transferability in algebraic signal processing through homomorphisms between algebraic signal models. Homomorphisms

researcharxiv-cs-lg

Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

arXiv:2609.36892v1 Announce Type: new Abstract: As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful

Improving Function Space Flow Matching with Kernel Optimal Transport

arXiv:2609.38049v1 Announce Type: new Abstract: Generative models for function-valued data, such as time series and solutions of partial differential equations, must learn distributions over infinite-

Multi-Task Dynamic Pricing in Credit Market with Contextual Information

arXiv:2410.14839v5 Announce Type: replace-cross Abstract: We study the dynamic pricing problem faced by a broker seeking to learn prices for a large number of credit market securities, such as corpora

On-Policy Parameter Update Direction Underlies Generalization in LLM Post-Training

arXiv:2609.36659v1 Announce Type: new Abstract: The strong generalization performance of on-policy post-training paradigms has motivated studies of their parameter update behaviors. However, these stu

Physics-Informed Multi-Agent Coordination for Hospital Patient Flow Optimization

arXiv:2609.37022v1 Announce Type: new Abstract: Efficient patient flow coordination across autonomous hospital departments is critical for mitigating overcrowding and balancing resource utilization. W