Search: “models”

Checkable NTK Positivity and Finite-Width Gradient Descent for Scalar- and Vector-Valued PINNs with Strong-Form, Weak-Form, and Nonlocal Linear Constraints

arXiv:2610.04357v1 Announce Type: new Abstract: We give checkable positive-definiteness criteria for the limiting neural tangent kernel (NTK) and high-probability finite-width gradient-descent guarant

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Safety

ClasSAE: Class-Aligned Sparse Autoencoders via Differentiable Feature-Class Affinity

DGX agent

arXiv:2610.04020v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) began as an unsupervised tool for decomposing neural representations into sparse, interpretable features, and are increasingl

safetyarxiv-cs-cv

6 Oct 2026

Collaborative Personalized Preference Alignment for LLMs under Data Deficiency

arXiv:2610.05898v1 Announce Type: new Abstract: Real-world users often exhibit highly heterogeneous preferences over multiple objectives for LLM responses. A lightweight aligner can tailor these respo

COMIC: Agentic Sketch Comedy Generation

arXiv:2603.11048v2 Announce Type: replace Abstract: We propose a fully automated AI system that produces short comedic videos similar to sketch shows such as Saturday Night Live. Starting from charact

agentsarxiv-cs-cv

Conditional Trajectory Peaks: Single-Pass Multimodal Policies over Action Chunks

arXiv:2610.06104v1 Announce Type: new Abstract: Multimodal imitation learning requires diverse executable futures under the same observation and consistent behavior across replanning cycles. We presen

safetyarxiv-cs-ro

ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution

arXiv:2610.04605v1 Announce Type: new Abstract: Many visual explanation methods in computer vision highlight pixel importance but struggle to link these low-level cues to semantically meaningful conce

safetyarxiv-cs-cv

Coupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery

arXiv:2610.04559v1 Announce Type: new Abstract: External causal reports can improve structure learning from limited observations, but their reliability varies across sources and variable pairs. We int

Critical Points of Degenerate Metrics on Algebraic Varieties: A Tale of Overparametrization

arXiv:2512.21029v2 Announce Type: replace-cross Abstract: We study the critical points over an algebraic variety of an optimization problem defined by a quadratic objective that is degenerate. This sc

DASH: Fast, Valid Counterfactuals for Deep Networks via Batched Directional Search

arXiv:2610.04783v1 Announce Type: new Abstract: Counterfactual explanations are most useful when they can be generated with low latency, remain close to the factual input, and satisfy input-domain, ca

Dataset-Free Compliant Humanoid Loco-Manipulation with Dynamic Online Posture

arXiv:2610.05678v1 Announce Type: new Abstract: Most humanoid loco-manipulation controllers require human motion data to learn whole-body coordination and posture, leaving policies reliant on external

safetyarxiv-cs-ro

Deep Learning for Sleep Heart Rate Estimation from Accelerometers: Toward Population-Scale Cardiac Insight Without Optical Sensors

arXiv:2610.06823v1 Announce Type: new Abstract: Large longitudinal cohorts often contain wrist accelerometry without optical heart-rate sensing, motivating recovery of cardiac information from motion

DexForge: High-Fidelity Physics-Informed Dexterous Retargeting

arXiv:2610.06331v1 Announce Type: new Abstract: Human demonstrations offer rich examples of precise dexterous manipulation and a promising source of robot training data. However, high-fidelity reprodu

tutorialsarxiv-cs-ro

Diffusion-Based Stress Testing of Overload Monitoring for Resilient Emergency Cellular Networks Using Internet CDR Proxies

arXiv:2610.04526v1 Announce Type: cross Abstract: Disasters can overload cellular control-plane signaling within minutes, yet fine-grained Radio Resource Control (RRC) or Next Generation (NG) Applicat

Distributionally Robust Deep Q-Learning

arXiv:2505.19058v2 Announce Type: replace Abstract: We propose a novel distributionally robust Q-learning algorithm for the non-tabular case accounting for continuous state spaces where the state tran

DNPush: Distributed Nonparallel Pushing Force Control of Multi-Robot Systems for Object Transportation

arXiv:2610.04764v1 Announce Type: new Abstract: This letter proposes DNPush, a Distributed Nonparallel Pushing force controller for cooperative object transport without inter-robot communication. Each

local-aiarxiv-cs-ro

Do Motion Tokenizers for Co-Speech Gesture Generation Encode Gesture Semantics?

arXiv:2610.03765v1 Announce Type: new Abstract: Discrete motion tokenizers encode motion as atomic units and are widely used for co-speech gesture generation. It remains unclear which motion propertie

tutorialsarxiv-cs-cv

Dynamic Quadtree Tokenization and Transformer for Adaptive Mesh PDE Forecasting

arXiv:2610.04044v1 Announce Type: new Abstract: The quadratic attention cost of Vision Transformers (ViTs) forces a trade-off between spatial resolution and rollout horizon, particularly for fine-scal

tutorialsarxiv-cs-cv

EDISCO: Equivariant DIScrete Diffusion for Euclidean Combinatorial Optimization

arXiv:2610.04953v1 Announce Type: new Abstract: Euclidean combinatorial optimization problems (ECOPs), such as the Traveling Salesman Problem (TSP) and Capacitated Vehicle Routing Problem (CVRP), poss

local-aiarxiv-cs-lg

Empirical Variational Autoencoder

arXiv:2610.06545v1 Announce Type: new Abstract: We present Empirical Variational Autoencoder, a general generative framework for continuous-valued (i.e., non-vector-quantized) sequences. EVA is based

Encoded but Not in Control: Revealing the Grounding Gap in Vision-Language Robot Policies

arXiv:2610.06235v1 Announce Type: cross Abstract: Instruction following is central to language-conditioned robot policies: language should determine what to do when the same scene permits multiple val

End-to-End Autonomous Recursive Arborescence Deformable Flow and Non-Linear Hemodynamics for Patient-Specific Coronary Centerline Extraction

arXiv:2610.05900v1 Announce Type: new Abstract: Extracting patient-specific vascular trees from volumetric medical images is fundamental to computational angiography and non-invasive hemodynamic asses

local-aiarxiv-cs-cv

Applications

Execution-Aligned Progressive Noise for Consistent Asynchronous Replanning in Generative Robot Policies

arXiv:2610.06090v1 Announce Type: new Abstract: Continuous asynchronous replanning is essential for real-time generative robot policies, but independent stochastic initialization can cause mode switch

applicationsarxiv-cs-ro

Fast Last-Iterate Convergence in Zero-Sum Markov Games with Bandit Feedback

arXiv:2610.05968v1 Announce Type: new Abstract: We study last-iterate convergence in unknown two-player zero-sum discounted Markov games with bandit feedback. The players learn independently along a s

FoSeRL: Formal Sequential Robustness Certification for Reinforcement Learning Policies

arXiv:2610.04754v1 Announce Type: new Abstract: Even a few action perturbations can substantially degrade the performance of a deployed decision policy. Certifying the resulting return loss is challen

From Social Reasoning to Embodied Interaction: An Agentic Framework for Social Robots

arXiv:2610.05964v1 Announce Type: new Abstract: Natural face-to-face human--robot interaction requires a robot to understand an evolving social situation, decide when to engage, and express its intent

agentsarxiv-cs-ro

FrontVeg V2: A Training-Free Software Framework for Foreground-Aware Zero-Shot Plant Trait Segmentation in High-Resolution Images of Trellised Crops

arXiv:2610.06575v1 Announce Type: new Abstract: FrontVeg V2 is an open-source, training-free software framework for foregroundaware zero-shot segmentation of plant traits in high-resolution images of

Game Plan: What AI can do for Football, and What Football can do for AI

arXiv:2011.09192v1 Announce Type: cross Abstract: The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individua

GeoFunFlow: Geometric function flow matching for joint probabilistic inference of physical fields and complex geometries

arXiv:2509.24117v2 Announce Type: replace Abstract: Inverse problems governed by partial differential equations (PDEs) arise widely in science and engineering, but are often ill-posed and limited by s

tutorialsarxiv-cs-lg

GFPack++: Attention-Driven Gradient Fields for Optimizing 2D Irregular Packing

arXiv:2406.07579v2 Announce Type: replace-cross Abstract: 2D irregular packing is a classic combinatorial optimization problem with various applications, such as material utilization and texture atlas

Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations

arXiv:2511.07734v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remai

local-aiarxiv-cs-lg

HeuFouFT: Task-Guided Metaheuristic Coordinate Search for Fourier Fine-Tuning

arXiv:2610.06437v1 Announce Type: new Abstract: We introduce Heuristic-Guided Fourier Fine-Tuning (HeuFouFT), a task-guided framework for selecting trainable frequency coordinates in Fourier fine-tuni

agentsarxiv-cs-lg

IBPA: Real-time Free-form Manifold Mesh Reconstruction via Incremental Ball Pivoting with Integrated Hole Detection

arXiv:2607.11627v2 Announce Type: replace-cross Abstract: Both Remotely Operated underwater Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs) are frequently deployed to acquire geometric bathy

agentsarxiv-cs-ro

Inverse Mixed-Integer Programming: Learning Constraints then Objective Functions

arXiv:2510.04455v3 Announce Type: replace-cross Abstract: Data-driven inverse optimization for mixed-integer linear programs (MILPs), which seeks to learn an objective function and constraints consist

tutorialsarxiv-cs-lg

Investigating Spatiotemporal Redundancy in Video Transformer for Collision Anticipation

arXiv:2610.04727v1 Announce Type: new Abstract: In worker-equipment proximity monitoring, video transformers are widely used for collision anticipation and have demonstrated strong performance. Howeve

JASPER: Special Session on Joint Reliability And Security Assessment of SPlit Computing for Edge Robustness

arXiv:2610.04396v1 Announce Type: cross Abstract: Split Computing (SC) enables efficient deployment of Deep Neural Networks (DNNs) by partitioning inference between edge devices and cloud servers. How

Joint Class-Time Learning for Video Classification with Multi-Instance Partial-Label Learning

arXiv:2610.06234v1 Announce Type: new Abstract: Multi-instance partial-label learning (MIPL) addresses inexact supervision in both the instance and label spaces, which can be applied to video classifi

Joint Estimation of Common-Slope Decay Rates and Spatial Amplitudes Using Parameterized Nonnegative Matrix Factorization

arXiv:2610.05549v1 Announce Type: new Abstract: We formulate joint estimation of common-slope decay rates and amplitudes from room impulse responses (RIRs) as parameterized nonnegative matrix factoriz

Kinematics-Centric Continuous Sign Language Retrieval with Gloss-Guided Boundary-Aware Alignment

arXiv:2610.05306v1 Announce Type: new Abstract: Sign language-text alignment remains a fundamental challenge for text-driven sign language understanding. Existing methods predominantly rely on appeara

local-aiarxiv-cs-cv

Label Agreement Does Not Measure Authorization

arXiv:2610.04544v1 Announce Type: cross Abstract: Many groups now delegate label ontology and metadata harmonization to agentic LLM pipelines. We built one and audited it. Our aggregate scores looked

agentsarxiv-cs-lg

Applications

Learning Granger Causality under Latent Confounding via Intervention-Induced Heterogeneity

arXiv:2510.19138v2 Announce Type: replace Abstract: Granger causality characterizes directed predictive dependencies in multivariate time series, but recovering such dependencies becomes challenging i

applicationsarxiv-cs-lg

LeAVJEPA: A Minimalist Architecture for Audio-Visual Self-Supervised Learning

arXiv:2610.06226v1 Announce Type: cross Abstract: Prior audio-visual self-supervised learning methods rely on mechanisms such as EMA target encoders, prediction heads, reconstruction decoders, and con

safetyarxiv-cs-cv

Leveraging Cost-effective Robotics for K-12 STEM Education through Water Quality Monitoring Tasks

arXiv:2610.04565v1 Announce Type: new Abstract: Engaging K-12 students in authentic scientific research remains a significant challenge, particularly at the intersection of environmental science and r

local-aiarxiv-cs-ro

Local Fisher Information Enables Sparse Causal Discovery

arXiv:2610.04291v1 Announce Type: cross Abstract: Sparse causal discovery calls for methods that exploit graph structure without estimating high-dimensional densities. We introduce Fisher Information

Local2Mesh: Spatially Localized Contour-to-Mesh for Left Ventricular Reconstruction from Sparse 2D Cardiac MRI

arXiv:2610.06052v1 Announce Type: new Abstract: Three-dimensional (3D) left ventricular (LV) reconstruction from sparse cardiac magnetic resonance (CMR) imaging remains challenging due to inter-slice

safetyarxiv-cs-cv

Low-Fidelity FDM Spectral Guidance for Neural Eigenvalue Solvers

arXiv:2610.04695v1 Announce Type: new Abstract: Operator eigenvalue problems appear throughout science. Classical methods usually discretize the operator into a matrix and then solve the resulting mat

MarvisNav: Making Memory Visible on Route Choices for Zero-Shot Object Navigation

arXiv:2610.06510v1 Announce Type: new Abstract: When searching for an object, people choose their next move by considering both likely target locations and places already explored. The current view ca

safetyarxiv-cs-ro

Masked Privileged-Information Distillation for Multimodal Skin Lesion Classification Under Missing Clinical Metadata

arXiv:2610.03991v1 Announce Type: new Abstract: Multimodal skin lesion classification combines clinical images with patient metadata to improve diagnostic accuracy. However, complete metadata availabl

Hardware

MC-Sparse: Deconstructing and Closing the Dense-Sparse Attention Gap in Diffusion Transformers

arXiv:2610.06801v1 Announce Type: new Abstract: Sparse attention is a primary approach to reducing the latency of diffusion transformers in long-sequence generation tasks, such as video and high-resol

hardwarearxiv-cs-cv