Search: “framework”

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

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Research

KineWorld: Action-Induced Transport Fields for Embodied World Modeling

DGX agent

arXiv:2610.06349v1 Announce Type: new Abstract: Embodied world models predict the visual consequences of candidate actions before execution. However, existing action-conditioned world models often ado

researcharxiv-cs-cv

6 Oct 2026

KVE-KD: Key Visual Evidence-Guided Knowledge Distillation for Vision-Language Models

arXiv:2610.03842v1 Announce Type: new Abstract: Knowledge distillation is crucial for deploying vision-language models on resource-constrained devices. However, existing methods typically impose unifo

Latent Similarity Gaussian Processes: A Theory-Grounded Approach to Personalized Suicide-Risk Forecasting for Clinical Decision-Support

arXiv:2610.06355v1 Announce Type: cross Abstract: Forecasting suicide risk is difficult due to the high heterogeneity of patients and the low base rate of suicide-related events (SREs). We present Lat

LD-EnFF: Latent-Dynamics Ensemble Flow Filtering for Data Assimilation with Sparse Observations

arXiv:2610.04034v1 Announce Type: new Abstract: Data assimilation combines model forecasts with noisy, incomplete observations to estimate the evolving state of a dynamical system. Existing methods fa

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

Learning Interpretable Differentiable Logic Networks for Tabular Regression

arXiv:2505.23615v2 Announce Type: replace Abstract: Neural networks (NNs) achieve outstanding performance in many domains; however, their decision processes are often opaque and their inference can be

Learning Latent Protein Languages for Autoregressive Generation

arXiv:2610.03978v1 Announce Type: new Abstract: Autoregressive transformers remain comparatively weak for protein sequence and structure generation. We study the role of target representation: amino a

Learning Subject-Specific Anatomical Representations via Manifold Expansion: Application to Accelerated Multi-Contrast MRI

arXiv:2610.04028v1 Announce Type: new Abstract: Clinical MRI routinely acquires multiple contrast-weighted images of the same anatomy for complementary tissue characterization. However, current accele

tutorialsarxiv-cs-cv

Learning to Read the Contextual Tokens in Diffusion Transformers

arXiv:2610.06844v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) jointly process visual and textual representations throughout generation. These models repeatedly update the

Learning Topological Representations of Protein Structure and Dynamics

arXiv:2606.14737v2 Announce Type: replace-cross Abstract: Modern protein representation models support tasks such as enzyme design and drug discovery, but their reliance on static data such as sequenc

tutorialsarxiv-cs-lg

LEON: Location Embeddings from OSM Neighborhoods via Hexagonal Graph Masked Autoencoders

arXiv:2610.05497v1 Announce Type: new Abstract: Geographic information systems increasingly rely on sophisticated spatial representation learning techniques to extract meaningful patterns from complex

tutorialsarxiv-cs-lg

Agents

Level-of-Token Diffusion

arXiv:2610.05816v1 Announce Type: new Abstract: Image and video diffusion models allocate equal computation to every region, even when the intended scene calls for varying levels of detail. The spatia

agentsarxiv-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

Lipschitz Thinking: Ten Years of Certifiable-by-Design Robust Neural Networks

arXiv:2610.06252v1 Announce Type: new Abstract: The Lipschitz property of a deep neural network provides a direct measure of its sensitivity to input perturbations and, when explicitly controlled, off

tutorialsarxiv-cs-lg

Localized Operator Learning with Adaptive Partition-of-Unity Mixture-of-Expert Networks

arXiv:2610.04708v1 Announce Type: new Abstract: Operator learning methods such as DeepONets and FNOs often struggle with PDE families featuring sharp interfaces, heterogeneous coefficients, and locali

Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks becaus

M^2-Occ: Resilient 3D Semantic Occupancy Prediction for Autonomous Driving with Incomplete Camera Inputs

model-releasesarxiv-cs-cv

arXiv:2603.09737v2 Announce Type: replace Abstract: Semantic occupancy prediction enables dense 3D geometric and semantic understanding for autonomous driving. However, existing camera-based approache

MAGEFormer: Learning Metric-Consistent Representations for Anisotropic CT Segmentation

arXiv:2610.04036v1 Announce Type: new Abstract: Vision Transformers (ViTs) have shown strong performance in volumetric segmentation, but their effectiveness on clinical CT is limited by an isotropic E

MagServo: Uncertainty-Resilient Hierarchical Magnetic Servoing via Learned Latent Representations

arXiv:2610.06046v1 Announce Type: new Abstract: Magnetic navigation provides contact-free and line-of-sight-independent feedback for robotic systems, yet existing approaches typically rely on explicit

researcharxiv-cs-ro

MambaVF: State Space Model for Efficient Video Fusion

arXiv:2602.06017v2 Announce Type: replace Abstract: Video fusion aims to integrate complementary information from multiple source videos while preserving temporal consistency. Effective modeling of te

MaRO-GS: Mask-Robust Object-Centric Gaussian Splatting from Inconsistent Multi-view Masks

arXiv:2610.06472v1 Announce Type: new Abstract: We address the challenge of accurate 3D object reconstruction from multi-view images in Gaussian Splatting. Existing object-level 3DGS methods reconstru

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

MedAD-R1: Consistency-Reinforced Policy Optimization for Interpretable Medical Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2602.01081v2 Announce Type: replace Abstract: Medical Anomaly Detection (MedAD) offers a promising direction for medical image analysis with Large Multimodal Models (LMMs). However, progress is

MemPilot: Orchestrating On-Demand Multimodal Memory Curation for LLM Agents

arXiv:2610.06830v1 Announce Type: cross Abstract: Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent me

MeSD: Multi-Evidence Self-Distillation for VideoLLM

arXiv:2610.06342v1 Announce Type: new Abstract: While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-lev

MIND: Microstructure INverse Design with Generative Hybrid Neural Representation

arXiv:2502.02607v2 Announce Type: replace Abstract: The inverse design of microstructures plays a pivotal role in optimizing metamaterials with specific, targeted physical properties. While traditiona

Minority Collective Action for User-Side Fairness

arXiv:2508.15374v3 Announce Type: replace Abstract: Machine learning models often preserve biases present in training data, leading to unfair treatment of certain minority groups. Despite an array of

ML-OPF-Bench: Benchmarking Machine Learning for Optimal Power Flow

model-releasesarxiv-cs-lg

arXiv:2610.04307v1 Announce Type: cross Abstract: Machine Learning (ML) methods promise a fast solution process for Optimal Power Flow (OPF). While inconsistent test cases, implementations, and evalua

Mobile-4DGS: Unified Static-Dynamic Real-time Mobile Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2610.05289v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable performance in novel view synthesis, yet deploying both static and dynamic Gaus

MoCAR: Motion-code Coordinate-aware AutoRegression for Continuous Trajectory Forecasting

arXiv:2610.06210v1 Announce Type: new Abstract: Autoregressive generation is natural for language, where predicted tokens can be directly reused as the next prediction state, but trajectory forecastin

MOXIE: Discovering Alternative Explanations for Biomedical Image Classifiers

arXiv:2610.04814v1 Announce Type: new Abstract: Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from one fixed image segmentation. This hides t

Applications

Multi-Marginal Schrodinger Bridge Matching

arXiv:2510.16587v2 Announce Type: replace-cross Abstract: Understanding the continuous evolution of populations from discrete temporal snapshots is a critical research challenge, particularly in field

applicationsarxiv-cs-lg

NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis

arXiv:2610.04722v1 Announce Type: new Abstract: Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, maki

NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI

arXiv:2610.06502v1 Announce Type: new Abstract: Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, an

No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401v1 Announce Type: new Abstract: Text-to-image diffusion models can generate prohibited content, which motivates concept erasure through machine unlearning. Most erasure methods interve

local-aiarxiv-cs-lg

Occlusion-Aware Contingency Safety-Critical Planning for Autonomous Driving

arXiv:2502.06359v3 Announce Type: replace Abstract: Ensuring safe driving while maintaining travel efficiency for autonomous vehicles in dynamic and occluded environments is a critical challenge. This

safetyarxiv-cs-ro

On Semi-Markov Suboptimality in Hierarchical Reinforcement Learning

arXiv:2610.05338v1 Announce Type: new Abstract: Hierarchical reinforcement learning uses temporally extended subtasks for exploration, yet committing to their execution can restrict both deployment an

One Tile, Multiple Instances: Rethinking MIL for Sparse Diagnostic Evidence

arXiv:2610.04853v1 Announce Type: new Abstract: In weakly supervised Whole Slide Image (WSI) classification, feature extractors typically compress each image tile into a single global embedding. Conse

Online Control via Counterfactual Tracking

model-releasesarxiv-cs-lg

arXiv:2607.13029v2 Announce Type: cross Abstract: We study online control of a known linear dynamical system with adversarial costs and bounded disturbances, measuring regret against a general class o

Online Target-less Radar-LiDAR-Camera Extrinsic Calibration via Joint Optimization

arXiv:2610.04552v1 Announce Type: new Abstract: Fusing radar, LiDAR, and camera enables robust perception in diverse and adverse conditions, but the fusion performance critically depends on accurate e

researcharxiv-cs-ro

Operational Abstractions of Neural Network Concepts via Topological Representations

arXiv:2610.05017v1 Announce Type: new Abstract: Concept-based methods provide a semantic level for interpreting and manipulating learned representations, but existing editing approaches are typically

Optimal Control with Learned Critics under Unmodeled State Dependencies

arXiv:2610.05359v1 Announce Type: new Abstract: Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analy

local-aiarxiv-cs-ro

Optimizer Geometry Sets the Pace: Spectral Learning Dynamics in Matrix Factorization

arXiv:2610.04249v1 Announce Type: new Abstract: Recent successes of matrix- and curvature-based optimizers have renewed interest in how update geometry shapes learning. These methods normalize or prec

PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents

model-releasesarxiv-cs-lg

arXiv:2610.05732v1 Announce Type: new Abstract: LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons. Existing methods provide limited support f

[Paper] WaveFront Decoding: Parallelized Self-Speculative Decoding for Looped Language Models

model-releasesr-localllama

Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequential recurrent-block calls per generated token s