Search: “applications”

VCURF: Virtual Camera-based Uncertainty of Radiance Fields

arXiv:2610.04076v1 Announce Type: new Abstract: Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel v

researcharxiv-cs-cv

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Vision-enabled detection of safety helmet compliance in construction zones

DGX agent

arXiv:2610.05756v1 Announce Type: new Abstract: In the rapidly evolving field of construction management, worker safety remains a top priority. This paper introduces an innovative vision-based system

safetyarxiv-cs-cv

6 Oct 2026

Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design

arXiv:2610.06400v1 Announce Type: new Abstract: Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, such as those encountered in sear

safetyarxiv-cs-ro

What Do Verifiable Rewards Teach Video-Language Models About Time? A Controlled Multi-Model Study

model-releasesarxiv-cs-cv

arXiv:2610.03792v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has produced large reasoning gains in language models, and verifiable video benchmarks make it app

When Does Longer Reasoning Help? Predicting Mathematical Reasoning Through Discovery and Execution

arXiv:2610.05322v1 Announce Type: new Abstract: Test-time compute can improve mathematical reasoning, but can short-budget runs predict how mathematical reasoning scales with additional compute? We in

A Generative Model of Complex Networks Using Graphons and Neural Inverse Operators

arXiv:2610.02439v1 Announce Type: new Abstract: Generative graph models are central to understanding and simulating complex networks. However, existing approaches have complementary strengths and limi

A GHOST in Long-Horizon Agents: Governance Hazard from Overlooked Safety Constraints across Turns

arXiv:2610.02664v1 Announce Type: new Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their exte

A Passive AI System for Verifying Physical State on Automated Liquid Handlers

arXiv:2610.02668v1 Announce Type: new Abstract: Automated liquid handlers execute digital protocols, but operators must assemble the deck and confirm that the physical setup matches the intended exper

researcharxiv-cs-ro

A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition

arXiv:2504.03432v4 Announce Type: replace-cross Abstract: Solving (Stampacchia) variational inequalities (SVIs) is a foundational problem at the heart of optimization. However, this expressivity comes

Ask, Relax, or Act? Evaluating Actionable Indeterminacy in LLM Preference Reasoning

arXiv:2610.03102v1 Announce Type: cross Abstract: An LLM agent can recognize uncertainty yet still choose the wrong next step: asking when action is already justified, or seeking clarification when th

Correcting Guided Diffusion Trajectories with Spectral Alignment

arXiv:2610.02753v1 Announce Type: cross Abstract: The practical success of conditional image generation hinges on fine-grained differences in condition alignment and visual fidelity. Classifier-free g

safetyarxiv-cs-ai

DeltaWorld: Physically Consistent Interactive World Simulators via Action-Conditioned Latent Increment Learning

model-releasesarxiv-cs-ro

arXiv:2610.02691v1 Announce Type: new Abstract: Interactive world simulators can provide scalable environments for robot planning, policy training, and evaluation by predicting action consequences whi

Local Ai

Electronic Density versus Geometry for Machine-Learned Molecular Absorption Spectra

arXiv:2610.03444v1 Announce Type: cross Abstract: Molecular optical absorption spectroscopy provides a direct probe of electronic structure and is widely used for molecular identification, interpretat

local-aiarxiv-cs-lg

Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing

arXiv:2509.20239v2 Announce Type: replace-cross Abstract: This paper investigates theoretical and methodological foundations for stochastic optimal control (SOC) in discrete time. We start formulating

Evaluation of Sampling Strategies and Physics-Informed Kolmogorov--Arnold Networks in Unbounded Domains

arXiv:2512.12074v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as an effective approach for solving partial differential equations (PDEs) by incorporating ph

FastOPD: On-Policy Distillation for Lightweight VLA Deployment

arXiv:2610.02832v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) foundation models have scaled rapidly to enhance manipulation performance and generalizability, but this scaling incurs h

safetyarxiv-cs-ai

Tutorials

How To Train Your World Model: Fine-tuning vs RAG for LM-based World Modeling

arXiv:2610.02542v1 Announce Type: new Abstract: World models (WMs) simulate the transition dynamics of environments, enabling agents to plan over the consequences of their actions. In text-based envir

tutorialsarxiv-cs-ai

Hybrid Machine Learning-Assisted Raman Spectroscopy with Generative Feature Augmentation for Pharmaceutical Identification

arXiv:2610.02224v1 Announce Type: new Abstract: Rapid and reliable identification of pharmaceutical residues is important for safeguarding public health, ensuring food safety, and enabling practical R

HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

arXiv:2610.03211v1 Announce Type: new Abstract: Self-supervised hypergraph representation learning can produce informative node embeddings, but existing methods often require deep encoders trained for

I got Qwen Flash Next Q4 running on a Mac Mini m5 64gb with ssd streaming

model-releasesr-localllama

Bit of a side project I wanted to share. The metrics are 17.5tks decode, 360tks prompt processing based testing against my normal ai usage. I tested a couple of new things others haven’t done (at leas

Learning Transferable Policies from Action-free Time Series Through Dynamical Embeddings

arXiv:2610.03065v1 Announce Type: new Abstract: Learning control from action-free recordings is challenging because intervention effects are unobserved and policies may exploit errors in reconstructed

Local Ai

LiteEMG-FM: An Efficient and Deployable Foundation Model for Robust EMG Sensing

arXiv:2610.02497v1 Announce Type: new Abstract: Electromyography (EMG) signals vary substantially across individuals, body regions, recording sessions, and sensing hardware, limiting the generalizatio

local-aiarxiv-cs-lg

Localized Conformal Safety Monitoring with Vision-Language Models for Autonomous Driving

arXiv:2610.02765v1 Announce Type: cross Abstract: Monitoring planned driving trajectories requires accurately estimating the collision likelihood with actors whose motion is itself impacted by the ego

LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios

arXiv:2602.03255v2 Announce Type: replace Abstract: Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluatin

Mental-R1: Aligning LLM Reasoning for Mental Health Assessment

arXiv:2606.13176v2 Announce Type: replace Abstract: Mental health problems such as anxiety, depression, and suicide remain urgent global challenges, where timely and accurate assessment is critical fo

safetyarxiv-cs-ai

Noise Sensitivity and Learning Lower Bounds for Hierarchical Functions

arXiv:2502.05073v4 Announce Type: replace-cross Abstract: Recent works explore deep learning's success by examining functions or data with hierarchical structure. To study the learning complexity of f

On the Convergence of Success Conditioning for Policy Optimization

arXiv:2610.03642v1 Announce Type: new Abstract: Success conditioning is a strategy for improving decision-making policies in stochastic environments; it updates a policy by increasing the probability

On Unlearning for Time-series Forecasting

arXiv:2610.02865v1 Announce Type: new Abstract: Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, w

Operator Calculus for Population-Based Optimization: Modular Convergence and Finite-Population Guarantees

arXiv:2606.14289v2 Announce Type: replace-cross Abstract: Population-based optimizers combine update rules such as mutation, selection, and recombination. When one rule changes, it is often unclear wh

Agents

Optimal Planning in a Dynamic World

arXiv:2610.03312v1 Announce Type: new Abstract: Background: We address the problem of planning when the set of feasible states or actions changes over time. For example, in the problem of path plannin

agentsarxiv-cs-ai

PaMIR: Open Benchmark of Public Credit-Default Datasets

arXiv:2610.03259v1 Announce Type: new Abstract: We release PaMIR (Public Arrival-ordered Measurement for Inference in Risk), an open benchmark for credit-default prediction when labels are scarce and

PLCWorld: Benchmarking LLM-Generated PLC Programs in Closed-Loop Plant Simulation

arXiv:2610.02982v1 Announce Type: new Abstract: Programmable logic controllers (PLCs) coordinate industrial equipment by reading sensor inputs and issuing control commands. Evaluating whether large la

PoCoFL: POlicy-COmpliant Federated Learning

arXiv:2610.03650v1 Announce Type: cross Abstract: Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to partici

Preserving Anatomical Continuity: Three-Stage Pipeline for Colon Segmentation in 3D Abdominal CT Scans

arXiv:2610.03467v1 Announce Type: cross Abstract: Accurate colon segmentation from CT images is essential for colorectal disease analysis, yet deep learning based methods often produce disconnected pr

researcharxiv-cs-ai

ProAR: Learning Prospective Reasoning with Autoregressive Video Models

arXiv:2610.03664v1 Announce Type: new Abstract: Autoregressive (AR) video models excel at causal generation, but their reliance on next-chunk prediction confines them to a short-sighted, reactive para

safetyarxiv-cs-cv

Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning

arXiv:2610.02615v1 Announce Type: new Abstract: Learning research, as one of its central goals, tries to measure, model, and understand how learning-problem properties affect average-case learning per

ReFract: Benchmarking Perspective Awareness in Language Model Agents with Text World Models

arXiv:2610.03356v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in high-stakes settings such as industrial maintenance and equipment fault troubleshooting,

Reliability of Probabilistic Emulation of Physical Systems

arXiv:2606.12997v2 Announce Type: replace Abstract: Two dominant approaches have emerged for generating probabilistic forecasts of physical systems: generative models, such as diffusion or flow matchi

Rethinking Epistemic Uncertainty in Node Classification through Information Growth

arXiv:2610.03418v1 Announce Type: cross Abstract: Epistemic uncertainty should decrease as additional information about the data-generating process (DGP) becomes available to the predictor. Yet, exist

researcharxiv-cs-ai

Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.02788v1 Announce Type: new Abstract: Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embod

Test-time Calibration Learning for Large Language Model Reasoning

arXiv:2610.02695v1 Announce Type: cross Abstract: Reliable large language models (LLMs) must not only produce accurate answers but also express confidence that faithfully reflects their probability of

The Neuro-Physical Inverter: A Modular Framework for Magnetotelluric Inversion Coupling Ensemble Conditioning with Residual Learning

arXiv:2610.03225v1 Announce Type: new Abstract: We present the Neuro-Physical Inverter (NPI), a modular, uncertainty-aware framework for geophysical inversion that couples ensemble-based conditioning

Agents

Toward SLM-based agentic task-tool intent matching

arXiv:2610.03213v1 Announce Type: new Abstract: Tool-equipped AI agents use tool calls to access data and act on external systems. Horizontal growth of agentic systems increases the number of these in

agentsarxiv-cs-ai

Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

arXiv:2610.03693v1 Announce Type: new Abstract: Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete re

researcharxiv-cs-ai

Understanding Clinical Cognitive Dialogues Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.34125v2 Announce Type: replace Abstract: In-person cognitive assessment is both a test and an interaction. Clinicians explain tasks, repair misunderstandings, and adapt to patient responses

Agents

What to expect at Infor Velocity Week: Join theCUBE Oct. 7

As agentic AI moves into production, the harder question is becoming what enterprises will actually trust it to do. Infor Inc. is betting that industry-specific context can help bridge that gap. The e

agentssiliconangle

When Is Accuracy Evidence? A Unified Theory of Generalisation, Validation, and Information Fusion

arXiv:2610.03465v1 Announce Type: cross Abstract: K-fold cross-validation (CV) is widely used as evidence of out-of-sample performance, although folds are neither independent experiments nor equally i

Hardware

Windfoil: Closed-Form Coverage for Real-Time and Differentiable Vector Graphics

arXiv:2610.02468v1 Announce Type: cross Abstract: We present Windfoil, a GPU-friendly algorithm that treats rasterisation and differentiable vector graphics as two sides of the same problem by evaluat

hardwarearxiv-cs-cv