Search: “governance”

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

arXiv:2606.10349v1 Announce Type: cross Abstract: We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-me

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Research

Population-Aware Physics-Informed Neural Particle Flow for Bayesian Update

DGX agent

arXiv:2606.10959v1 Announce Type: new Abstract: Physics-informed neural particle flow (PINPF) learns a deterministic transport field that moves particles from a prior distribution toward a Bayesian po

researcharxiv-cs-lg

10 Jun 2026

Local Ai

Post-Quantum Secure Federated DeFi for Inclusive Banking

arXiv:2606.10658v1 Announce Type: cross Abstract: Recent advances in error-corrected qubits have accelerated the timeline for practical quantum computing. It poses a threat to cryptographic primitives

local-aiarxiv-cs-ai

Rank Collapse, Fixed Points, and the Renormalization Group Structure of MLP Residual Networks

arXiv:2606.10324v1 Announce Type: new Abstract: The analogy between deep neural network forward passes and renormalization group (RG) flows has been repeatedly noted in the literature, but existing tr

Robust Active Learning for Few-Shot Example Selection in Text-to-SQL

arXiv:2606.10125v1 Announce Type: cross Abstract: Few-shot example retrieval is the dominant paradigm for grounding large language models (LLMs) in domain-specific text-to-SQL systems. However, the qu

Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows

arXiv:2606.09857v1 Announce Type: new Abstract: Reduced-order models (ROMs) provide an efficient surrogate for complex multiscale systems, but their predictive accuracy is often compromised by truncat

Hardware

Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey

arXiv:2606.10706v1 Announce Type: cross Abstract: Resource constraints increasingly determine what can be trained, fine-tuned, and deployed in large language models (LLMs), yet efficiency is often stu

hardwarearxiv-cs-ai

When to Align, When to Predict: A Phase Diagram for Multimodal Learning

arXiv:2606.11190v1 Announce Type: new Abstract: Cross-modal alignment (CA) and cross-modal prediction (CP) are the dominant paradigms for multimodal representation learning, yet there is no systematic

safetyarxiv-cs-lg

A Machine Learning-Enhanced Hopf-Cole Formulation for Nonlinear Gas Flow in Porous Media

arXiv:2603.11250v2 Announce Type: replace-cross Abstract: Accurate modeling of gas flow through porous media is critical for many technological applications, including reservoir performance prediction

A practical probabilistic framework for deformable image registration uncertainty in radiotherapy dose propagation

arXiv:2606.09253v1 Announce Type: new Abstract: Deformable image registration (DIR) is widely used in radiotherapy for dose propagation and accumulation, but uncertainty in the underlying deformation

safetyarxiv-cs-cv

Agent Economics: An Entropy-Controlled Pluralistic Alignment Framework for Preventing Artificial Hivemind in Autonomous Agents

arXiv:2606.09039v1 Announce Type: new Abstract: This study proposes the Behavioral Protocol Framework (BPF), an entropy-controlled pluralistic alignment framework designed to address two critical chal

AI Assurance in UK Defence: Challenges in Operationalising JSP 936

arXiv:2606.09414v1 Announce Type: cross Abstract: This report examines practical challenges in operationalising JSP 936 Part 1 for AI assurance in UK Defence. Using a structured interpretive review of

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

model-releasesarxiv-cs-ai

arXiv:2606.08761v1 Announce Type: cross Abstract: W4A4 quantization promises full utilization of INT4 Tensor Cores, yet group dequantization overhead on CUDA Cores has driven existing systems to mixed

Automating the Expert Eye: A System-Agnostic Deep Learning Framework for Rare Event Discovery in Imbalanced Force Spectroscopy

arXiv:2606.09541v1 Announce Type: cross Abstract: Single-Molecule Force Spectroscopy (SMFS) provides unprecedented insights into biomolecular mechanics, yet the high-throughput generation of force-ext

Autonomous Obstacle Removal for Excavators through Policy Learning with Particle Simulation

arXiv:2606.09183v1 Announce Type: new Abstract: Autonomous obstacle removal from the ground is an important earthwork task, but this is difficult to automate because an excavator must adapt its excava

safetyarxiv-cs-ro

Tutorials

Blockchain Infrastructure for Intelligent Cyber--Physical--Social Systems:Post-Quantum Security, Interoperability, and Trustworthy Data Economies in the Era of Embodied AI

arXiv:2606.06895v1 Announce Type: cross Abstract: The deployment of embodied artificial intelligence via world-model-based robotics presents a transformative opportunity for blockchain infrastructure,

tutorialsarxiv-cs-ai

Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution

arXiv:2606.08800v1 Announce Type: new Abstract: In high-stakes settings such as brand compliance, clinical care, and content moderation, machine learning cannot be deployed as opaque oracles: practiti

Can Data Work be Reparative?

arXiv:2606.09408v1 Announce Type: cross Abstract: We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and b

Contrast encodes inductive bias: separating slow noise from dynamics in predictive representation learning

arXiv:2606.07770v1 Announce Type: new Abstract: Self-supervised methods that learn representations and predict dynamics fully in the latent space, such as JEPA, have been shown to confuse slowly varyi

safetyarxiv-cs-lg

Convergence Bound and Critical Batch Size of Muon Optimizer

arXiv:2507.01598v5 Announce Type: replace Abstract: Muon, a recently proposed optimizer that leverages the inherent matrix structure of neural network parameters, has demonstrated strong empirical per

Decomposable Neuro Symbolic Regression

arXiv:2511.04124v3 Announce Type: replace Abstract: Symbolic regression (SR) models complex systems by discovering mathematical expressions that capture underlying relationships in observed data. Howe

Emergence via Phase Transitions: Mechanism Landscapes and Universal Convergence Across Complex Systems

arXiv:2606.07563v1 Announce Type: cross Abstract: Across machine learning, biology, and physics, independently evolving systems often converge toward strikingly similar high-level structures despite r

Tutorials

Explaining Data Mixing Scaling Laws

arXiv:2606.08167v1 Announce Type: cross Abstract: Recent research has established empirical scaling laws to predict model performance on multi-domain data mixtures. However, a theoretical understandin

tutorialsarxiv-cs-ai

Local Ai

Federated Large Language Models: Current Progress and Future Directions

arXiv:2409.15723v3 Announce Type: replace Abstract: Large Language Models have achieved impressive performance across diverse applications, yet their training typically depends on centralized data col

local-aiarxiv-cs-lg

Formalizing Learning from Language Feedback with Provable Guarantees

arXiv:2506.10341v2 Announce Type: replace Abstract: Interactively learning from observation and language feedback is an increasingly studied area driven by the emergence of large language model (LLM)

Frankenstein in the Pipeline: Computational Epistemicide in Facial Recognition

arXiv:2606.07628v1 Announce Type: cross Abstract: While the eugenic roots of computer vision are well-documented in critical technology studies, less attention has been paid to the operational mechani

safetyarxiv-cs-cv

Inferring hidden forcing in a biological oscillator using Kolmogorov-Arnold networks

arXiv:2606.08479v1 Announce Type: new Abstract: Inferring the forces that drive a dynamical system from partial observations is a fundamental challenge across physics, particularly when distinct under

Instrumental convergence and power-seeking

arXiv:2606.08832v1 Announce Type: new Abstract: Recent years have seen increasing concern that artificial intelligence may soon pose an existential risk to humanity. One leading ground for concern is

LCAM: A Framework for Diagnosing Interactional Alignment Failures in Con-versational AI

arXiv:2606.08131v1 Announce Type: cross Abstract: Conversational AI is increasingly used for advice, interpretation, reassurance, and decision support in contexts where users may be vulnerable, uncert

Learning Dynamics Reveal a Hierarchy of Weight-Induced Layerwise Gram Metrics

arXiv:2606.09744v1 Announce Type: new Abstract: We study feed-forward ReLU networks with fixed readout and quadratic loss. The aim is to rewrite gradient descent not primarily as a dynamics in weight

Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution

arXiv:2606.08904v1 Announce Type: new Abstract: Macro placement is a fundamental step in modern chip physical design, playing a crucial role in determining the solution quality of high-dimensional com

Pointwise Complexity for Gaussian Fields: Upper Envelopes, Algorithmic Lower Bounds, and Separation

arXiv:2606.07931v1 Announce Type: cross Abstract: We prove a variance-aware pointwise majorizing-measure theorem for centered Gaussian processes. Classical generic chaining characterizes the scalar qu

Post-AGI Economies: Superposition and the Second Fundamental Theorem of Welfare Economics

arXiv:2606.08267v1 Announce Type: cross Abstract: The classical Second Welfare Theorem decentralizes any Pareto efficient allocation through prices and transfers under convexity and regularity. In pos

QnRL: Quantum-Native Reinforcement Learning

arXiv:2606.08276v1 Announce Type: cross Abstract: Quantum reinforcement learning (QRL) is a promising approach to learn effective decision strategies across several applications with stochastic enviro

safetyarxiv-cs-lg

Reachability and asymptotics of Gaussian Transformer dynamics

arXiv:2606.07600v1 Announce Type: cross Abstract: We formulate data propagation through the Transformer, the machine learning architecture powering large language models, as a nonlinear control system

Semantic Quorum Assurance: Collective Certification for Non-Deterministic AI Infrastructure

arXiv:2606.08021v1 Announce Type: cross Abstract: As large language model (LLM) agents are integrated into autonomous cloud operations, distributed systems face a semantic reliability problem: propose

'So There's a Catch-22 Here': How Early Adopters Who Build Multi-Agent LLM Systems Conceptualize Transparency

arXiv:2606.08323v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are rapidly emerging, yet transparency, a cornerstone of responsible AI, remains under-defined in these

SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)

arXiv:2606.08372v1 Announce Type: cross Abstract: Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat

Tutorials

Sustainability and Artificial Intelligence: Necessary, Challenging, and Promising Intersections

arXiv:2606.09006v1 Announce Type: cross Abstract: Both digital economy and digital technology researchers increasingly recognize the need to better address the role that artificial intelligence (AI) p

tutorialsarxiv-cs-ai

Agents

Syll: Open-Source Personal Automation with Cross-Surface Execution

arXiv:2606.07594v1 Announce Type: new Abstract: Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface an

agentsarxiv-cs-ai

TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking

model-releasesarxiv-cs-ai

arXiv:2602.03224v2 Announce Type: replace Abstract: Test-time evolution of agent memory represents a pivotal paradigm for advancing AGI, as it strengthens complex reasoning through experience accumula

Testing the Black Box: Structural Barriers to Independent Evaluation of Consumer-Facing Health LLMs

arXiv:2606.08483v1 Announce Type: new Abstract: Background: Consumer-facing large language models are now a common source of health information, and they interpret and personalize responses rather tha

The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting

arXiv:2602.03395v4 Announce Type: replace Abstract: While deep learning has revolutionized financial forecasting through sophisticated architectures, the design of the supervision signal itself is rar

Topological Neural Operators

arXiv:2606.09806v1 Announce Type: cross Abstract: We introduce Topological Neural Operators (TNOs), a principled framework for operator learning on cell complexes that lifts neural operators (NOs) fro

When Are Neural Interaction Discoveries Real? Identifiability, Recoverability, and a Pre-Fit Diagnostic

arXiv:2606.08390v1 Announce Type: new Abstract: When a neural time-series model reports that one variable modulates another's effect on a target, is the discovered interaction a property of the data o

When Do Local Score Models Extrapolate Across Size? A Diagnostic Theory and Benchmark

arXiv:2606.09705v1 Announce Type: new Abstract: Scientific generative modeling often requires size transfer, where models trained on small systems are evaluated on larger ones. While translation-invar

Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation

arXiv:2606.07113v1 Announce Type: new Abstract: Large language models are rapidly becoming infrastructural components in high-stakes institutional settings, including public administration, legal reas

8 Jun 2026

Multilingual Multi-Speaker Unit Vocoders: A Systematic Analysis of Discrete Speech Representations

arXiv:2606.06740v1 Announce Type: cross Abstract: Discrete speech units obtained via k-means clustering of self supervised embeddings entangle phonetic, speaker, and language information, causing spea