Search: “governance”

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models

arXiv:2605.09630v1 Announce Type: new Abstract: Tokenizer-free language models eliminate the tokenizer step of the language modeling pipeline by operating directly on bytes; patch-based variants furth

researcharxiv-cs-cl

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Local Ai

Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets

DGX agent

arXiv:2605.09209v1 Announce Type: cross Abstract: We study optimistic bilevel optimization when the lower-level problem has a non-isolated manifold of minimizers. In this setting, the hyper-objective

local-aiarxiv-cs-ai

12 May 2026

Selection Plateau and a Sparsity-Dependent Hierarchy of Pruning Features

arXiv:2605.09345v1 Announce Type: new Abstract: We identify a Selection Plateau phenomenon in one-shot neural network pruning: all rank-monotone weight scorers converge to identical accuracy at fixed

Sharp feature-learning transitions and Bayes-optimal neural scaling laws in extensive-width networks

arXiv:2605.10395v1 Announce Type: cross Abstract: We study the information-theoretic limits of learning a one-hidden-layer teacher network with hierarchical features from noisy queries, in the context

Hardware

SkillEvolver: Skill Learning as a Meta-Skill

arXiv:2605.10500v1 Announce Type: new Abstract: Agent skills today are static artifact: authored once -- by human curation or one-shot generation from parametric knowledge -- and then consumed unchang

hardwarearxiv-cs-ai

Agents

SkillMaster: Toward Autonomous Skill Mastery in LLM Agents

arXiv:2605.08693v1 Announce Type: new Abstract: Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selec

agentsarxiv-cs-ai

Social Determinants of Health and Fentanyl Overdose Mortality Across US Counties: An XGBoost and SHAP Analysis Identifying Silent Risk Counties and Treatment Deserts

arXiv:2605.08230v1 Announce Type: new Abstract: Background: Fentanyl overdose deaths are still increasing across the U.S. We do not fully understand which county-level social and structural conditions

Strategic commitments shape collective cybersecurity under AI inequality

arXiv:2605.09415v1 Announce Type: new Abstract: The growing integration of AI into cybersecurity is reshaping the balance between attackers and defenders. When access to advanced AI-enabled defence to

Switching-Geometry Analysis of Deflated Q-Value Iteration

arXiv:2605.10811v1 Announce Type: cross Abstract: This paper develops a joint spectral radius (JSR) framework for analyzing rank-one deflated Q-value iteration (Q-VI) in discounted Markov decision pro

safetyarxiv-cs-ai

Tutorials

The finite expression method for turbulent dynamics with high-order moment recovery

arXiv:2605.10687v1 Announce Type: new Abstract: Turbulent dynamical systems are characterized by nonlinear interactions and stochastic effects that generate coupled statistical quantities, such as non

tutorialsarxiv-cs-lg

The Invisible Handshake: Persistent Overpricing by Adaptive Market Agents

arXiv:2510.15995v3 Announce Type: replace-cross Abstract: We study overpricing in a repeated game between two representative agents: a market maker, who controls market liquidity, and a market taker,

The Open-Box Fallacy: Why AI Deployment Needs a Calibrated Verification Regime

arXiv:2605.10601v1 Announce Type: new Abstract: AI deployment in sensitive domains such as health care, credit, employment, and criminal justice is often treated as unsafe to authorize until model int

The Procrustean Bed of Time Series: The Optimization Bias in Point-wise Loss Functions

arXiv:2512.18610v3 Announce Type: replace Abstract: Intuitively, a more deterministic time series should be easier to forecast. However, point-wise loss functions (e.g., MSE and MAE), serving as diffe

Tokens-per-Parameter Coverage Is Critical for Robust LLM Scaling Law Extrapolation

arXiv:2605.08541v1 Announce Type: new Abstract: Neural scaling laws approximate a language model's loss as a power-law function of parameter count N and token count D. Following Chinchilla-style compu

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse

model-releasesarxiv-cs-cv

arXiv:2605.09965v1 Announce Type: new Abstract: The real world unfolds along a single set of physics laws, yet human intelligence demonstrates a remarkable capacity to generalize experiences from this

Understanding Asynchronous Inference Methods for Vision-Language-Action Models

arXiv:2605.08168v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models offer a promising path to generalist robot control, but their inference latency causes observation staleness when

Applications

Unlocking air traffic flow prediction through microscopic aircraft-state modeling

arXiv:2605.10083v1 Announce Type: new Abstract: Short-term air traffic flow prediction in terminal airspace is essential for proactive air traffic management. Existing approaches predominantly model t

applicationsarxiv-cs-lg

VORT: Adaptive Power-Law Memory for NLP Transformers

arXiv:2605.08966v1 Announce Type: new Abstract: Standard Transformers impose near-exponential decay on the influence of distant tokens, conflicting with the power-law structure of long-range dependenc

Local Ai

WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms

arXiv:2605.09173v1 Announce Type: cross Abstract: Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under f

local-aiarxiv-cs-ai

What should post-training optimize? A test-time scaling law perspective

arXiv:2605.10716v1 Announce Type: new Abstract: Large language models are increasingly deployed with test-time strategies: sample N responses, score them with a reward model or verifier, and return th

When Does Non-Uniform Replay Matter in Reinforcement Learning?

arXiv:2605.10236v1 Announce Type: cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains unclear when and why non-uniform repla

3D tomography of exchange phase in a Si/SiGe quantum dot device

arXiv:2603.16025v2 Announce Type: replace-cross Abstract: The exchange interaction is a foundational building block for the operation of spin-based quantum processors. Extracting the exchange interact

researcharxiv-cs-cv

Adaptive Negative Reinforcement for LLM Reasoning:Dynamically Balancing Correction and Diversity in RLVR

arXiv:2605.07137v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a highly effective method for improving the reasoning abilities of Large Language Mod

AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning

arXiv:2605.07121v1 Announce Type: new Abstract: Temporal knowledge graphs (TKGs) represent time-stamped relational facts and support a wide range of reasoning tasks over evolving events. However, exis

AffineLens: Capturing the Continuous Piecewise Affine Functions of Neural Networks

arXiv:2605.06218v2 Announce Type: replace Abstract: Piecewise affine neural networks (PANNs) provide a principled geometric perspective on neural network expressivity by characterizing the input--outp

Agents

Agentic AI and the Industrialization of Cyber Offense: Forecast, Consequences, and Defensive Priorities for Enterprises and the Mittelstand

arXiv:2605.06713v1 Announce Type: cross Abstract: Agentic AI systems can plan, call tools, inspect code, interact with web applications, and coordinate multi-step workflows. These same capabilities ch

agentsarxiv-cs-ai

Beyond GSD-as-Token: Continuous Scale Conditioning for Remote Sensing VLMs

model-releasesarxiv-cs-cv

arXiv:2605.07562v1 Announce Type: new Abstract: Remote sensing vision-language models (RS-VLMs) face a fundamental mismatch with natural-image counterparts: the same geographic object exhibits radical

CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation

arXiv:2605.07098v1 Announce Type: new Abstract: Crash simulation is a cornerstone of modern vehicle development because it reduces the need for costly physical prototypes, accelerates safety-driven de

CARMEN: CORDIC-Accelerated Resource-Efficient Multi-Precision Inference Engine for Deep Learning

arXiv:2605.06878v1 Announce Type: cross Abstract: This paper presents CARMEN, a runtime-adaptive, CORDIC-accelerated multi-precision vector engine for resource-efficient deep learning inference. The k

researcharxiv-cs-ro

Continuous First, Discrete Later: VQ-VAEs Without Dimensional Collapse

arXiv:2605.06870v1 Announce Type: new Abstract: While many approaches to improve VQ-VAE performance focus on codebook size and utilization, the effect of dimensional collapse, where trained VQ-VAE rep

Does Your Neural Network Extrapolate? Feature Engineering as Identifiability Bias for OOD Generalization

arXiv:2605.07483v1 Announce Type: cross Abstract: Successful deep neural networks discover salient features of data. We show when and why they fail to learn out-of-distribution (OOD)-relevant represen

safetyarxiv-cs-ai

Applications

Exploring CoCo Challenges in ML Engineering Teams: Insights From the Semiconductor Industry

arXiv:2605.07389v1 Announce Type: cross Abstract: The integration of machine learning (ML) into complex software systems has increased challenges in collaboration and communication (CoCo) of the teams

applicationsarxiv-cs-lg

GAD in the Wild: Benchmarking Graph Anomaly Detection under Realistic Deployment Challenges

arXiv:2605.07133v1 Announce Type: cross Abstract: Graph Anomaly Detection (GAD) is a critical task in graph machine learning with vital applications in financial fraud detection and social platform go

Local Ai

Generating training datasets for legal chatbots in Korean

arXiv:2605.07432v1 Announce Type: new Abstract: Chatbots are robots that can communicate with humans using text or voice signals. Legal chatbots improve access to justice, since legal representation a

local-aiarxiv-cs-cl

How Big Should a Wireless Foundation Model Be?

arXiv:2605.07266v1 Announce Type: cross Abstract: Wireless foundation models are rapidly emerging as a key enabler of AI-native communication systems, yet a fundamental question remains unanswered: ho

How Far Are VLMs from Privacy Awareness in the Physical World? An Empirical Study

arXiv:2605.05340v2 Announce Type: replace-cross Abstract: As Vision-Language Models (VLMs) are increasingly deployed as autonomous cognitive cores for embodied assistants, evaluating their privacy awa

Applications

LAMES: A Large-Scale and Artisanal Mining Environmental Segmentation Dataset

arXiv:2605.07740v1 Announce Type: new Abstract: Mining operations are of utmost importance to the economy of some nations. However, such operations result in land-use change, very high energy consumpt

applicationsarxiv-cs-cv

Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD?

arXiv:2605.07072v1 Announce Type: new Abstract: Poisson subsampling is the default sampling scheme in differentially private machine learning, largely because its unstructured randomness yields tracta

MAST: A Multi-fidelity Augmented Surrogate model via Spatial Trust-weighting

arXiv:2602.20974v2 Announce Type: replace Abstract: In engineering design and scientific computing, computational cost and predictive accuracy are intrinsically coupled. High-fidelity simulations prov

Mechanistic Interpretability with Sparse Autoencoder Neural Operators

arXiv:2509.03738v4 Announce Type: replace-cross Abstract: We introduce sparse autoencoder neural operators (SAE-NOs), a new class of sparse autoencoders that operate in function spaces rather than fix

Modular Lie Algebraic PDE Control of Multibody Flexible Manipulators

model-releasesarxiv-cs-ro

arXiv:2605.06709v1 Announce Type: new Abstract: This paper addresses PDE-based control for flexible multibody robotic systems, presenting a subsystem-based framework for serial manipulators with arbit

Tutorials

Neurosymbolic Framework for Concept-Driven Logical Reasoning in Skeleton-Based Human Action Recognition

arXiv:2605.07140v1 Announce Type: cross Abstract: Skeleton-based human activity recognition has achieved strong empirical performance, yet most existing models remain black boxes and difficult to inte

tutorialsarxiv-cs-ai

On the Role of Strain and Vorticity in Numerical Integration Error for Flow Matching

arXiv:2605.06680v1 Announce Type: cross Abstract: Flow matching generates data by integrating a learned velocity field, where the number of integration steps (NFE) directly determines inference cost.

researcharxiv-cs-cv

PAIR-Former: Budgeted Relational Multi-Instance Learning for Functional miRNA Target Prediction

arXiv:2602.00465v3 Announce Type: replace-cross Abstract: Functional miRNA--mRNA targeting is a large-bag prediction problem where each transcript yields a heavy-tailed pool of candidate target sites

Pretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification

arXiv:2603.00223v2 Announce Type: replace Abstract: We investigate a quantum-inspired approach to supervised multi-class classification based on the Pretty Good Measurement (PGM), viewed as an operato

researcharxiv-cs-cv

Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs

arXiv:2605.08053v1 Announce Type: new Abstract: Reinforcement learning (RL) for exponential-utility optimization in discounted Markov decision processes (MDPs) lacks principled value-based algorithms.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation

arXiv:2605.07760v1 Announce Type: new Abstract: Platform content moderation applies explicit policy rules and context-dependent conditions to decide whether user content is allowed, restricted, or rem

S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models

model-releasesarxiv-cs-cl

arXiv:2503.05085v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have fundamentally reshaped speech-to-speech (S2S) systems, enabling increasingly natural spoken int