Search: “models”

Generalized PINN-Based Inverse Estimation of Spatially Varying Heat Transfer Coefficients with Transfer Learning

arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va

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Research

Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets

DGX agent

arXiv:2610.15110v1 Announce Type: cross Abstract: Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image datasets, long algorithm traini

researcharxiv-cs-cv

14 Oct 2026

Getting Space Right: Agentic Rewards for Image Generation

arXiv:2610.14852v1 Announce Type: new Abstract: Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accura

safetyarxiv-cs-cv

Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach

arXiv:2610.15064v1 Announce Type: new Abstract: The world has seen several threats that include resource depletion, food security, poverty and inequality, difficulties associated with urbanization, mi

Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction

arXiv:2610.16272v1 Announce Type: new Abstract: Feed-forward reconstruction recovers camera poses and dense geometry from image sets whose views are assumed to come from a single scene. In practice, u

local-aiarxiv-cs-cv

Applications

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat

applicationsarxiv-cs-lg

Hierarchical Multi-Agent Reasoning Systems for Knowledge-Grounded Material Substitution

arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can

agentsarxiv-cs-lg

HiPAD: A Unified Gait, Audio-Visual, and Personality Fusion Network for Depression Detection, with a Hierarchical Personality Ablation and the Calibration Limits of Domain-Adapted LLMs

arXiv:2610.14961v1 Announce Type: cross Abstract: We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and

Honeycomb Crystal in a Mass-Asymmetric Electron-Hole Bilayer

arXiv:2610.17030v1 Announce Type: cross Abstract: A two-dimensional electron gas in a uniform neutralizing background forms a triangular Wigner crystal at low density. In a strongly mass-asymmetric el

local-aiarxiv-cs-lg

How Shared Representations Become Specialized: Formation, Maintenance, and Latent Susceptibility

arXiv:2610.15830v1 Announce Type: new Abstract: When several predictions use the same internal representation, information about some targets can remain easier to recover than information about others

Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics

arXiv:2610.15760v1 Announce Type: new Abstract: Multiscale structure is central to time series forecasting: temporal signals contain slowly varying trends, intermediate seasonal patterns, and high-fre

Images Talk Back: Guiding MMDiTs by Suppressing Image-to-Text Feedback

arXiv:2610.13941v2 Announce Type: replace Abstract: Multimodal diffusion transformers (MMDiTs) allow the evolving image to update internal text representations through joint attention. These represent

safetyarxiv-cs-cv

Integrating Feature Understandability into Feature Selection for Human-Centred Tabular Explanations

arXiv:2610.16627v1 Announce Type: cross Abstract: Existing human-centred XAI research predominantly evaluates explanations after they have been generated. However, this fails to provide actionable ins

Jevolution: A Framework for Studying Communication and Collective Dynamics in AI Agents

arXiv:2610.14449v1 Announce Type: cross Abstract: Experiments with remote decision-making agents depend on more than the policy: the world may change during inference, the simulator determines which a

local-aiarxiv-cs-lg

Koopman DCM: Unstable Eigenfunctions as Data-driven Representations for Legged Balancing

arXiv:2607.18760v2 Announce Type: replace Abstract: In legged locomotion, divergent components of motion (DCMs) have emerged as characteristic states for balance control. They isolate the unstable mod

researcharxiv-cs-ro

Learning Reachability-Based Safety Representations for Real-Time Robot Navigation in Unknown and Dynamic Environments

arXiv:2610.16522v1 Announce Type: cross Abstract: Safe robot navigation in unknown, dynamic environments requires more than geometric collision checking: a robot still far from an obstacle may be unab

Learning Temporal Evidence Selection for Video Anomaly Understanding

arXiv:2610.16299v1 Announce Type: new Abstract: Video anomaly understanding (VAU) aims to generate language-level interpretations of anomalous events in long videos, requiring visual evidence that sup

LERR-Nav: Learning to Coordinate Exploration, Recovery, and Reminiscing for Object Navigation

arXiv:2610.15362v1 Announce Type: new Abstract: Object Navigation in unseen environments remains a fundamental challenge in embodied AI, as it requires agents to generalize visual and spatial reasonin

safetyarxiv-cs-ro

Lost in Contrast: Instruction-Preserving Decoding for Reliable Visual Question Answering

arXiv:2610.16722v1 Announce Type: cross Abstract: Visual contrastive decoding corrects answers using the prediction difference between the original image and a reference condition, yet the same contra

Hardware

LunaTP: Enabling Efficient and Scalable Tensor Product for Equivariant MLIPs

arXiv:2610.18393v1 Announce Type: cross Abstract: Equivariant machine learning interatomic potentials (MLIPs) promise atomistic simulations with accuracy approaching that of quantum-mechanical calcula

hardwarearxiv-cs-lg

Measuring Variable Importance Using Proportional Inclusive Marginal Effects

arXiv:2610.17053v1 Announce Type: cross Abstract: Shapley-based measures are widely used for measuring variable importance in statistics and machine learning. However, these measures have a serious is

MemAct: Streaming Spatial Understanding with Memory and Active Exploration

arXiv:2610.17640v1 Announce Type: new Abstract: Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents

MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation

arXiv:2610.17354v1 Announce Type: new Abstract: Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which

Mixing Regularization for Average-Reward Q-Learning and Q-Planning

arXiv:2610.14988v1 Announce Type: new Abstract: The average-reward setting for reinforcement learning is challenging because its Bellman operator is known to contract in span only when the underlying

Multi-modal Representation Fusion for Long-term Microsurgical Anastomosis Trajectory Anticipation

arXiv:2610.14492v1 Announce Type: cross Abstract: Microsurgical anastomosis is one of the most challenging and sophisticated procedures for surgical robotics, requiring accurate manipulation of surgic

Neural Evidence and Behavioural Welfare Economics: When Can Neuroeconomics Inform Policy?

arXiv:2511.19548v2 Announce Type: replace Abstract: Neuroeconomics appears to offer welfare economics an evidential supplement, since neural data may help distinguish choices that express genuine pref

Novel View Synthesis using DDIM Inversion

arXiv:2508.10688v3 Announce Type: replace Abstract: Single-image novel view synthesis requires viewpoint-dependent structural changes while retaining source-scene information and inferring unobserved

On the Optimality of Random Features under General Conditions: Misspecified Cases and Robust Learning

arXiv:2610.18333v1 Announce Type: cross Abstract: Random features provide a standard approach to scaling kernel methods to large datasets by approximating the kernel with a finite-dimensional feature

Hardware

PACC: Protocol-Aware Cross-Layer Compression for Compact Network Traffic Representation

arXiv:2602.08331v2 Announce Type: replace-cross Abstract: Network traffic classification underpins network security and management but faces growing challenges from pervasive encryption and evolving p

hardwarearxiv-cs-lg

PaceReasoner: Label-Free Learning to Answer Briefly from Long Reasoning

arXiv:2610.17900v1 Announce Type: cross Abstract: Extended chain-of-thought reasoning improves problem-solving performance but increases inference cost and latency, motivating more accurate answers wi

Panoramic Out-of-Distribution Segmentation

arXiv:2505.03539v4 Announce Type: replace Abstract: Panoramic imaging enables capturing 360{eg} images with an ultra-wide Field-of-View (FoV) for dense omnidirectional perception, which is critical to

PathPilot: An Adaptive Question-Conditioned Multi-Magnification Navigation Agent for Whole-Slide Image Analysis

arXiv:2610.16734v1 Announce Type: new Abstract: The diagnostic capability of WSI agents relies on effective slide navigation to identify diagnostically relevant regions and efficiently integrate evide

Perfect Reconstruction Cannot Show Whether Two Codebooks on a VAE's Latent Space Agree

arXiv:2610.14012v1 Announce Type: new Abstract: Many systems read the latent space of a variational autoencoder (VAE) as discrete codes, and rely on each latent being read back as the code it was writ

Persistence Positional Encoding: A Minimal Transformer Recipe for Persistence Diagrams

arXiv:2610.17848v1 Announce Type: new Abstract: Persistence diagrams (PDs) represent multiscale topological information as multisets of birth-death pairs (b,d). How best to use them with Transformers,

Physics-Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity

arXiv:2507.05291v2 Announce Type: replace Abstract: We propose a physics-informed machine learning framework called P-DivGNN to reconstruct local stress fields at the micro-scale, in the context of mu

local-aiarxiv-cs-lg

Pick the Mixture, Not the Samples: Combinatorial Data Selection for LLMs

arXiv:2610.14028v1 Announce Type: new Abstract: Data selection for LLM fine-tuning faces two facts about real training: data pools draw from many distinct domains, and evaluation spans diverse tasks.

PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection

arXiv:2509.19774v3 Announce Type: replace Abstract: Electrocardiography (ECG) is the clinical gold standard for cardiovascular disease (CVD) assessment, yet continuous monitoring is constrained by the

Predicting Audio Popularity: A Comparative Study of Metadata and Acoustic Features Across Music and Sound Effects

arXiv:2610.16809v1 Announce Type: cross Abstract: This study addresses the prediction of audio popularity on an online sharing platform by leveraging both metadata and acoustic feature representations

Predicting Mental Health Help-Seeking Behaviour on Reddit: A Survival Analysis of Linguistic and Behavioural Signals

arXiv:2610.16983v1 Announce Type: cross Abstract: Most prior work on predicting mental health help-seeking treats it as post-hoc classification of users already active in clinical communities, which c

PreSO: Privileged Representation Isolation for On-Policy Self-Distillation

arXiv:2610.14001v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a self-teacher conditioned on privileged information to turn the sparse outcome signal of reinforcement learning

Applications

Prior-Fitted and Frozen Scorers for Multimodal Contrastive Learning

arXiv:2610.14770v1 Announce Type: new Abstract: Multimodal contrastive learning typically relies on manually specified scoring functions, such as cosine similarity, to quantify the similarity between

applicationsarxiv-cs-lg

Probabilistic Multi-Source Data Selection via Learnable Categorical Priors: Variance Reduction and Guaranteed Derandomization

arXiv:2610.14942v1 Announce Type: new Abstract: Bilevel data selection is a fundamental task with numerous applications in machine learning and statistics. A common strategy for tackling this problem

ProGAN-Based Synthetic Image Generation for Industrial Visual Inspection of Metallic Parts

arXiv:2610.16287v1 Announce Type: new Abstract: Automated visual inspection is essential for efficient repair and recycling of metallic components. AI-based defect detection is a strong fit. However,

Applications

Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

arXiv:2512.03923v3 Announce Type: replace Abstract: Solving reservoir seepage partial differential equations (PDEs) is critical for hydrocarbon development optimization and production forecasting. Con

applicationsarxiv-cs-lg

Regime-Aware Router Learning for Multi-Domain Medical Image Generation with Diffusion Experts

arXiv:2610.16082v1 Announce Type: new Abstract: Heterogeneous medical image data motivate domain-specialized diffusion experts, but expert specialization alone does not determine how their predictions

Registration is a Representation Problem: Solving Whole-Body PET/CT Registration

arXiv:2610.18804v1 Announce Type: new Abstract: Raw image intensities are a poor surrogate for similarity across images in correspondence problems. Further, while auxiliary segmentation labels can pro

safetyarxiv-cs-cv

Representation Geometry and Inductive Biases in Quantum Classifiers across Classical Visual Benchmarks

arXiv:2610.17722v1 Announce Type: cross Abstract: Quantum Machine Learning (QML) has a theoretical advantage over classical algorithms for specific synthetic data that is computationally hard. However

Hardware

Resource-Efficient 3D Shape and Orientation Estimation of Road Users using Roadside RGB Camera and 3D Radar

arXiv:2610.18417v1 Announce Type: new Abstract: End-to-end deep learning pipelines for camera-radar 3D object detection are well established in driver assistance systems and autonomous vehicles; howev

hardwarearxiv-cs-cv