Search: “governance”

Task-Aligned Self-Supervised Learning for Medical Image Analysis: A Systematic Review and Practical Design Guidelines

arXiv:2605.23995v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has emerged as a promising paradigm for addressing the annotation bottleneck in medical imaging by learning representat

safetyarxiv-cs-ai

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Agents

Test-Time Deep Thinking to Explore Implicit Rules

DGX agent

arXiv:2605.24828v1 Announce Type: new Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming increasingly vital. However, these agents often fail in

agentsarxiv-cs-ai

26 May 2026

Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation

arXiv:2605.25488v1 Announce Type: cross Abstract: Audio-driven talking-head generation has achieved remarkable progress with recent models such as AniTalker, FLOAT, and Sonic. Despite their success, m

The Normalized Maximum Likelihood for Regular Non-Smooth Models: Measure-Theoretic Foundations and Geometric Sampling

arXiv:2605.24477v1 Announce Type: new Abstract: The Normalized Maximum Likelihood (NML) codelength, or stochastic complexity, represents a principled criterion for universal coding. While recent coare

Tools

> … [W]e keep finding things that are mysterious, even unsettling. We find structures that mirror results from human neuroscience. We find e…

> … [W]e keep finding things that are mysterious, even unsettling. We find structures that mirror results from human neuroscience. We find evidence of introspection. We find internal states that funct

toolsboris-cherny--x

AI Assurance: A Comprehensive Testing Strategy for Enterprise AI Systems

arXiv:2605.23459v1 Announce Type: cross Abstract: Enterprise AI systems, built on large language models, retrieval pipelines and autonomous agents, introduce a class of risks that traditional software

agentsarxiv-cs-ai

Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering

model-releasesarxiv-cs-cl

arXiv:2605.23497v1 Announce Type: new Abstract: Large language models are increasingly used for legal research, yet their fixed training cutoffs and reliance on static parametric knowledge are at odds

Asymmetric Scaling Laws from Sparse Features

arXiv:2605.23591v1 Announce Type: cross Abstract: We introduce a model for neural scaling laws under sparse activations. In the model, test loss is often dominated by rare coordinates that are never o

Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum

arXiv:2510.00526v3 Announce Type: replace Abstract: Supervised fine-tuning (SFT) is the standard approach for post-training large language models (LLMs), yet it often shows limited generalization. We

researcharxiv-cs-cl

Brain-LLM Alignment Tracks Training Data, Not Typology

arXiv:2605.23032v1 Announce Type: cross Abstract: Brain-LLM alignment is well established in English, yet the brain's language network is neuroanatomically universal across languages. Does alignment a

Tutorials

CALAD: Channel-Aware contrastive Learning for multivariate time series Anomaly Detection

arXiv:2605.23139v1 Announce Type: cross Abstract: Multivariate time series anomaly detection has become increasingly important in real-world applications, where labeled data are often scarce. Many exi

tutorialsarxiv-cs-ai

Computable Fairness: Boltzmann-Softmax Control for AI Resource Allocation

arXiv:2605.22827v1 Announce Type: cross Abstract: In large-scale AI systems, allocating scarce resources such as GPU compute time and bandwidth among multiple agents is a critical challenge. Conventio

Cultural Adaptation in Large Language Models for Political Discourse

model-releasesarxiv-cs-cl

arXiv:2605.23332v1 Announce Type: new Abstract: The integration of large language models into political discourse analysis creates new opportunities for comparative research, policy analysis, and civi

Hardware

DFSAttn: Dynamic Fine-grained Sparse Attention for Efficient Video Generation

arXiv:2605.23445v1 Announce Type: new Abstract: Diffusion transformers have achieved remarkable success in high-quality video generation, yet their reliance on spatiotemporal 3D full attention incurs

hardwarearxiv-cs-cv

Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned

arXiv:2602.13241v2 Announce Type: replace-cross Abstract: Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a susta

safetyarxiv-cs-ai

FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning

arXiv:2605.22898v1 Announce Type: new Abstract: Federated learning protocols face a structural trilemma: canonical server-based aggregation~ite{mcmahan2017} creates a single point of failure and gradi

safetyarxiv-cs-lg

Instance-Optimal Estimation with Multiple LLM Judges on a Budget

arXiv:2605.23362v1 Announce Type: new Abstract: Evaluating large language models increasingly relies on LLM-as-a-judge protocols, but such evaluations remain costly: different judges have different pr

Learning Through Noise: Why Subliminal Learning Works and When It Fails

arXiv:2605.23645v1 Announce Type: cross Abstract: In the context of artificial neural networks, subliminal learning refers to the transfer of task-relevant knowledge or unintended biases from teacher

researcharxiv-cs-ai

LLM Sparsity Prior for Robust Feature Selection

arXiv:2605.23102v1 Announce Type: cross Abstract: Large language models (LLMs) offer a scalable mechanism to elicit domain-informed prior information for high-dimensional variable selection. However,

PrefBench: Evaluating Zero-Shot LLM Agents in Hidden-Preference Personalized Pricing Negotiations

arXiv:2605.22855v1 Announce Type: cross Abstract: Personalized pricing negotiations are a challenging testbed for LLM agents because successful interaction does not guarantee profitable decision makin

Local Ai

SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models

arXiv:2605.23345v1 Announce Type: new Abstract: Interactive world models for first-person shooter (FPS) games must resolve high-frequency overlapping control signals at every frame without disrupting

local-aiarxiv-cs-cv

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules

arXiv:2605.22859v1 Announce Type: cross Abstract: Automated sleep staging is commonly approached as a supervised machine learning problem, with deep learning methods dominating recent research. While

researcharxiv-cs-ai

The UK, outpaced by the US and China in AI, is turning to experimental technologies like neuromorphic computing in search of computing sovereignty (Charles Clover/Financial Times)

Charles Clover / Financial Times: The UK, outpaced by the US and China in AI, is turning to experimental technologies like neuromorphic computing in search of computing sovereignty — Military capabili

industrytechmeme

clarifying: the issue is that alignment instructions and don’t pass, and the emotional weight that some people attach to LLMs can cause chal…

Gary Marcus discusses how alignment instructions in large language models often fail to work as intended, and argues that the emotional attachment some people develop toward LLMs can create additional

safetygary-marcus--x

24 May 2026

Quartermaster, which is building an analytics platform and a SmartMast, with sensors on a ship's mast to relay real-time maritime data, raised a $43M Series A (Sean O'Kane/TechCrunch)

Sean O'Kane / TechCrunch: Quartermaster, which is building an analytics platform and a SmartMast, with sensors on a ship's mast to relay real-time maritime data, raised a $43M Series A — Oceans — to s

industrytechmeme

24 May 2026

Applications

A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction

arXiv:2605.21528v1 Announce Type: new Abstract: Accurate and reproducible disease risk prediction remains challenging due to heterogeneous features, limited samples, and severe class imbalance. This s

applicationsarxiv-cs-lg

Applications

Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations

arXiv:2605.22275v1 Announce Type: new Abstract: Kernel methods are typically formulated under the assumption of exact, noise-free access to the Gram matrix. However, in emerging settings such as quant

applicationsarxiv-cs-lg

Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review

model-releasesarxiv-cs-lg

arXiv:2605.21903v1 Announce Type: cross Abstract: The integration of machine learning with domain-specific physics is transforming the design, monitoring, and control of electricity systems, where dat

Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model

arXiv:2605.21568v1 Announce Type: new Abstract: In this work, we extend the Equilibrium Propagation framework to skew-gradient systems and show an equivalence between deep Energy-Based Models and Hami

Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs

arXiv:2605.21994v1 Announce Type: new Abstract: GraphRAG conditions language models on subgraphs retrieved from knowledge graphs, encoded via message-passing GNNs. Because these encoders entangle node

On Statistical Estimation of Edge-Reinforced Random Walks

arXiv:2503.06115v2 Announce Type: replace-cross Abstract: Reinforced random walks (RRWs), including vertex-reinforced random walks (VRRWs) and edge-reinforced random walks (ERRWs), model random walks

Applications

Physics-Informed Generative Solver: Bridging Data-Driven Priors and Conservation Laws for Stable Spatiotemporal Field Reconstruction

arXiv:2605.22338v1 Announce Type: new Abstract: Reconstructing continuous physical fields from sparse measurements is a central inverse problem, but data-driven generative models can produce states th

applicationsarxiv-cs-lg

Physics Priors Offer Useful Accuracy-Carbon Trade-Offs in Spatio-Temporal Forecasting

arXiv:2509.24517v2 Announce Type: replace Abstract: Development of modern deep learning methods has been driven primarily by the push for improving model efficacy (accuracy metrics). This sole focus o

Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective

model-releasesarxiv-cs-lg

arXiv:2605.21692v1 Announce Type: new Abstract: Characterizing precisely the asymptotic generalization error of neural networks using parameters that can be estimated efficiently is a crucial problem

What are the Right Symmetries for Formal Theorem Proving?

arXiv:2605.22257v1 Announce Type: new Abstract: Formal theorem provers based on large language models (LLMs) are highly sensitive to superficial variations in problem representation: semantically equi

safetyarxiv-cs-lg

Tutorials

A Tutorial on Diffusion Theory: From Differential Equations to Diffusion Models

arXiv:2605.22586v1 Announce Type: cross Abstract: This tutorial develops diffusion models from the viewpoint of differential equations. We begin with the conditional Gaussian forward process and show

tutorialsarxiv-cs-cl

Analytical and Experimental Force Analysis of a Soft Linear Pneumatic Actuator

arXiv:2605.21836v1 Announce Type: new Abstract: Soft sleeve actuators (SSAs) have recently been developed as a pneumatic actuation approach for wearable and assistive robotic systems. By integrating t

researcharxiv-cs-ro

Local Ai

Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries

arXiv:2605.21712v1 Announce Type: new Abstract: Transportation safety analysis requires integrating crash records, roadway attributes, and geospatial data through GIS-based workflows, but access remai

local-aiarxiv-cs-cl

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning

model-releasesarxiv-cs-cl

arXiv:2605.22138v1 Announce Type: cross Abstract: How should an agent decide when and how to plan? A dominant approach builds agents as reactive policies with adaptive computation (e.g., chain-of-thou

Elon, stop trying to make Grok happen

There is a harsh truth about Elon Musk's 'truth-seeking' AI chatbot Grok: It's not very good, and not many people are using it. That's the takeaway of a new Reuters report, which found that Grok barel

industrythe-verge-ai

Enabling Regulatory Multi-Agent Collaboration: Architecture, Challenges, and Solutions

arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent c

agentsarxiv-cs-ai

Energy-Gated Attention: Spectral Salience as an Inductive Bias for Transformer Attention

arXiv:2605.21842v1 Announce Type: cross Abstract: Standard transformer attention computes pairwise similarity between queries and keys, treating all tokens as equally salient regardless of their intri

safetyarxiv-cs-cl

From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)

arXiv:2605.20608v1 Announce Type: new Abstract: Realizing Level 4/5 Autonomous Networks (AN) demands a shift from static automation to agent-native intelligence. Current operations, reliant on rigid s

agentsarxiv-cs-ai

How Databricks Genie democratizes data access in financial services

Databricks Genie is a tool designed to democratize data access within financial services organizations by enabling non-technical users to query and analyze data through natural language interfaces. Th

industrydatabricks

Tutorials

HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control

arXiv:2602.03205v2 Announce Type: replace Abstract: While current humanoid whole-body control frameworks predominantly rely on the static environment assumptions, addressing tasks characterized by hig

tutorialsarxiv-cs-ro

Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow

arXiv:2605.21980v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) represent a significant leap towards empathetic agents, demonstrating remarkable capabilities in emotion understand

researcharxiv-cs-cv

Observability for any agent, anywhere: Production-ready tracing with OpenTelemetry & Unity Catalog on Databricks

Databricks provides production-ready observability solutions for AI agents using OpenTelemetry integration and Unity Catalog, enabling comprehensive tracing and monitoring across distributed agent dep

agentsdatabricks

Open-source AI is pulling Dell’s entire portfolio into play

Open-source AI agents are changing software development, empowering both developers and citizen builders alike in a domain once reserved for professional engineers. But the influx of agents now spread

agentssiliconangle