Search: “models”

Geometry-Aware Deep Congruence Networks for Manifold Learning in Cross-Subject Motor Imagery

arXiv:2511.18940v3 Announce Type: replace Abstract: Cross-subject motor imagery decoding remains a fundamental challenge in EEG-based brain-computer interfaces due to substantial inter-subject variabi

safetyarxiv-cs-lg

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Research

Grounded Event Extraction from SEC 8-K Filings with a Fine-Grained Taxonomy

DGX agent

arXiv:2607.08346v1 Announce Type: new Abstract: Form 8-K filings are the primary channel through which U.S. public companies disclose material events, but the SEC item codes attached to them are coars

researcharxiv-cs-cl

10 Jul 2026

Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents

arXiv:2607.08448v1 Announce Type: new Abstract: Language-conditioned manipulation requires both precise contact-rich control and robust reasoning over language, scenes, and long horizons. End-to-end V

local-aiarxiv-cs-ro

(heta_l, heta_u)-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces

arXiv:2503.08394v5 Announce Type: replace-cross Abstract: Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering

applicationsarxiv-cs-lg

Holographic Neural PCFG for Unsupervised Parsing

arXiv:2607.08063v1 Announce Type: new Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve

researcharxiv-cs-cl

How Do I Know What to Say Next? Barenholtz's Autogenerative Theory as an Enrichment of Harrisean Integrationism

arXiv:2607.07891v1 Announce Type: cross Abstract: Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational appro

HSA: Hierarchical Slot Attention for Multi-granularity Scene-Decomposition

arXiv:2607.08249v1 Announce Type: new Abstract: Slot attention is a powerful framework for object-centric learning, decomposing visual scenes into latent slots through iterative competitive attention.

safetyarxiv-cs-cv

Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment

arXiv:2603.19186v3 Announce Type: replace Abstract: Randomized controlled trials (RCTs) are the gold standard for estimating treatment effects, yet they are often underpowered for detecting effect het

safetyarxiv-cs-lg

INTENT: An LSTM Framework for Vehicle Intention Prediction in Intersection Scenarios with Comprehensive Ablation Analysis

arXiv:2607.08316v1 Announce Type: new Abstract: Vehicle intention prediction is a pivotal aspect in the agility and safety of autonomous vehicles in all driving scenarios; if genuine enhancement of au

Koopman-informed recurrent neural networks

arXiv:2410.23467v3 Announce Type: replace Abstract: Recurrent neural networks are a successful neural architecture for many time-dependent problems, including time series analysis, forecasting, and mo

applicationsarxiv-cs-lg

Agents

MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction

arXiv:2607.08080v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) requires jointly identifying (aspect, opinion, sentiment) triples from a given review sentence. While large l

agentsarxiv-cs-cl

MLQENABLER: Enabling Secure Machine Learning Queries over Encrypted Database in Cloud Computing

arXiv:2607.08197v1 Announce Type: cross Abstract: In cloud computing, the public cloud service providers (CSPs) can provide cloud storage as the primary service while providing additional machine lear

researcharxiv-cs-lg

Monocular Vision Based Control Framework for Grasping

arXiv:2607.07897v1 Announce Type: new Abstract: Grasping in unstructured environments requires handling objects with widely different mechanical properties, from soft and deformable items to rigid eve

applicationsarxiv-cs-ro

Neural non-canonical Hamiltonian dynamics for long-time simulations

arXiv:2510.01788v2 Announce Type: replace Abstract: This work focuses on learning non-canonical Hamiltonian dynamics from data, where long-term predictions require the preservation of structure both i

tutorialsarxiv-cs-lg

PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation

arXiv:2510.19475v2 Announce Type: replace Abstract: Monocular 3D human pose estimation remains a fundamentally ill-posed inverse problem due to the inherent depth ambiguity in 2D-to-3D lifting. While

SAGA: Stable Acceleration Guidance for Autoregressive Video Generation

arXiv:2607.08020v1 Announce Type: new Abstract: Autoregressive video diffusion enables efficient streaming and long-horizon video generation, but repeatedly reusing generated latents as causal context

SPL: Orchestrating Workflows with Declarative Deterministic-Probabilistic Composition

arXiv:2607.07727v1 Announce Type: cross Abstract: We present SPL (Structured Prompt Language), a declarative language that composes deterministic and probabilistic computation modes in a single specif

local-aiarxiv-cs-cl

SpO_2 Predictor-Guided Stage-Wise Time-Frequency Reconstruction of Low-Quality Dual-Wavelength PPG for Oxygen Saturation Estimation

arXiv:2607.07996v1 Announce Type: cross Abstract: Continuous oxygen saturation (SpO_2) estimation from wearable photoplethysmography (PPG) is important for long-term health monitoring, but low-quality

Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning

arXiv:2607.08444v1 Announce Type: cross Abstract: In this paper, we study quantile-based distributional reinforcement learning from the perspective of statistical efficiency. We focus on distributiona

safetyarxiv-cs-lg

Structure Learning on Clustered Data

arXiv:2607.08238v1 Announce Type: new Abstract: Recent algorithmic advances have made directed acyclic graph (DAG) structure learning scalable for causal discovery. Yet, the currently available techni

local-aiarxiv-cs-lg

Agents

The Context Access Divide: Interaction-Level Architecture as a Complementary Dimension of Agentic Inequality

arXiv:2607.08495v1 Announce Type: cross Abstract: Sharp et al. (2025) introduce 'agentic inequality' as a framework for analyzing disparities in access to AI agents across three dimensions: availabili

agentsarxiv-cs-ai

Towards Soft Robotic Exogloves for Musculoskeletal Manipulation to Reduce Pain and Spasticity

arXiv:2607.07958v1 Announce Type: new Abstract: Hand spasticity and resulting pain affect 12 million people worldwide, including stroke survivors, arthritis patients, and those with other muscle and n

researcharxiv-cs-ro

Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution

arXiv:2607.07716v1 Announce Type: cross Abstract: Temporal graphs are ubiquitous in real-world applications and Temporal Graph Networks (TGNs) have achieved superior predictive accuracy. Understanding

applicationsarxiv-cs-ai

AA-ViT: Anatomically Aware Vision Transformer with Structural and Frequency Guidance for Contrast Enhanced Brain MRI Synthesis

arXiv:2607.07553v1 Announce Type: new Abstract: Accurate tumour localization and diagnosis is a critical component of clinical care for brain cancers. Magnetic Resonance Imaging (MRI) is the most comm

local-aiarxiv-cs-cv

ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation

arXiv:2607.07640v1 Announce Type: cross Abstract: Deep learning has significantly advanced time series imputation, yet most existing architectures primarily rely on localized temporal context within t

local-aiarxiv-cs-ai

An Edge-aware Prompt-enhanced SAM for Ultrasound Image Segmentation

arXiv:2607.07240v1 Announce Type: new Abstract: Ultrasound image segmentation is essential for delineating anatomical structures and lesions, providing the foundation for accurate diagnosis. While the

tutorialsarxiv-cs-cv

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training

arXiv:2607.07292v1 Announce Type: cross Abstract: Accurately estimating urban carbon emissions is critical for sustainable urban planning, yet many existing approaches remain difficult to apply consis

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning

arXiv:2607.07565v1 Announce Type: cross Abstract: One-shot federated learning (OSFL) addresses the communication overhead of federated learning by limiting training to a single round, but doing so wit

ColorFM: An Optimization-to-Learning Framework for Color Transfer via Flow Matching

arXiv:2607.07119v1 Announce Type: new Abstract: Color transfer aims to align the color distribution of a source image with that of a reference image while preserving structural and semantic consistenc

Agents

CoMind: Understanding Collaborative Human Activity from Multiple Minds and Views

arXiv:2607.06691v1 Announce Type: new Abstract: Human-human collaboration is a fundamental aspect of everyday life, essential to success in a wide range of goal-directed activities from household task

agentsarxiv-cs-cv

Compass: Prostate Cancer Detection Needs Multi-View Context

arXiv:2607.06919v1 Announce Type: new Abstract: Artificial intelligence (AI) analysis of micro-ultrasound (muUS) has shown promise for prostate cancer (PCa) detection. However, most existing AI method

Continuous and large-scale: ELEANOR, the soft architected arm inspired by the elephant trunk

arXiv:2607.07622v1 Announce Type: new Abstract: The elephant trunk is a dexterous and versatile manipulator whose performance is still unmatched in robotics. In previous works, modularity was prioriti

researcharxiv-cs-ro

Creating Power Distribution Network Layouts Using Generative Adversarial Networks and Image-Based Representations

arXiv:2607.06622v1 Announce Type: cross Abstract: Utilities increasingly rely on planning and operational tools to cope with the increased penetrations of distributed energy resources, yet the lack of

tutorialsarxiv-cs-lg

Creativity from Friction: Human-AI Interaction for Exploratory Structural Design

arXiv:2607.07521v1 Announce Type: cross Abstract: AI agents that generate final answers based on user input often do not meet the needs of creative fields. Fields such as structural design and archite

D2PO: Optimizing Diffusion Samplers via Dynamic Preference

arXiv:2607.06609v1 Announce Type: cross Abstract: We propose D2PO (Dynamic Direct Preference Optimization), a principled framework for optimizing diffusion sampling policies with respect to timestep s

DiffCVE: Diffusion-based Compressed Video Enhancement

arXiv:2607.07195v1 Announce Type: new Abstract: Perceptual quality enhancement of severely compressed videos remains challenging due to complex artifact patterns and substantial information loss. Rece

Hardware

Efficient Long-Horizon Learning for Learned Optimization

arXiv:2607.06772v1 Announce Type: new Abstract: Learned optimization aims to improve upon hand-designed optimizers (e.g., Adam and Muon) by meta-learning small neural network optimizers over a distrib

hardwarearxiv-cs-lg

EventVGGT: Exploring Cross-Modal Distillation for Consistent Event-based Depth Estimation

arXiv:2603.09385v2 Announce Type: replace Abstract: Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approa

Feynman Kac Reweighted Schrodinger Bridge Matching for Surface-Based Tau PET Harmonization

arXiv:2606.17420v2 Announce Type: replace-cross Abstract: Tau positron emission tomography (PET) is widely used for the in vivo characterization of disease stage and progression in Alzheimer's disease

Generating Personalized Lower-Limb Kinematics Across Walking Speeds Using Subject-Conditioned Diffusion

arXiv:2607.07533v1 Announce Type: new Abstract: Personalizing exoskeleton assistance requires user-specific gait data across many locomotor tasks, yet collecting this data demands repeated motion capt

researcharxiv-cs-ro

GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM

arXiv:2607.07452v1 Announce Type: new Abstract: Dense visual SLAM is a fundamental problem in robotics. Recent advances in 3DGS have demonstrated its potential for dense SLAM. Existing 3DGS frameworks

applicationsarxiv-cs-ro

GP-4DGS: Probabilistic 4D Gaussian Splatting from Monocular Video via Variational Gaussian Processes

arXiv:2604.02915v2 Announce Type: replace Abstract: We present GP-4DGS, a novel framework that integrates Gaussian Processes (GPs) into 4D Gaussian Splatting (4DGS) for principled probabilistic modeli

Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance

arXiv:2607.07665v1 Announce Type: new Abstract: Classifier-free guidance (CFG) is the standard way to strengthen class-conditioning in diffusion and flow-matching samplers, yet at large guidance it ov

researcharxiv-cs-lg

Hardware-aware Graph Neural Networks prunning for embedded event-based vision

arXiv:2607.06739v1 Announce Type: new Abstract: Event-based cameras are gaining popularity as the sensor of choice for mobile robotics, due to their high performance in dynamic environments. However,

HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies

arXiv:2512.05693v2 Announce Type: replace-cross Abstract: Generalist vision--language--action (VLA) policies are typically trained on heterogeneous mixtures of robot demonstrations spanning diverse em

tutorialsarxiv-cs-ai

HumAIN: Human-Aware Implicit Social Robot Navigation

arXiv:2607.07357v1 Announce Type: cross Abstract: Effective social robot navigation requires sensitivity to human behavior, often revealed through subtle skeletal cues like gait and orientation. We pr

Hardware

Intrinsic-Noise Consolidation: A Doob-Barrier-Conditioned Diffusion Turns Analog Device Noise into a Continual-Learning Resource

arXiv:2607.06924v1 Announce Type: new Abstract: On analog neuromorphic hardware, intrinsic device noise is normally an accuracy tax. We ask whether it can instead consolidate memories. We cast per-syn

hardwarearxiv-cs-lg

Learning social norms enhances compatibility in dynamic human-AI coordination

arXiv:2607.07021v1 Announce Type: new Abstract: Humans continuously coordinate with others in dynamic interactions, often through implicit, hard-to-quantify social norms that act as shared tacit expec