Search: “research”

Contour Field based Elliptical Shape Prior for the Segment Anything Model

arXiv:2504.12556v2 Announce Type: replace Abstract: The elliptical shape prior information plays a vital role in improving the accuracy of image segmentation for specific tasks in medical and natural

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

CoSeP: Complementary Separability Pruning via Class-Separability Clustering

DGX agent

arXiv:2505.13225v2 Announce Type: replace Abstract: Neural network pruning aims to compress models for efficient deployment, yet two fundamental challenges remain. First, many methods rely on per-comp

researcharxiv-cs-cv

9 Jun 2026

Cosmo3DFlow: Wavelet Flow Matching for Spatial-to-Spectral Compression in Reconstructing the Early Universe

arXiv:2602.10172v2 Announce Type: replace-cross Abstract: Reconstructing the early universe from the evolved present-day universe is a challenging and computationally demanding problem in modern astro

CRAG: Can 3D Generative Models Help 3D Assembly?

arXiv:2602.22629v2 Announce Type: replace Abstract: Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, huma

Crop Recommendation and Agricultural Query Answering System Using Spatio-Temporal Graph Neural Networks and Hybrid Retrieval Augmentation

arXiv:2606.09160v1 Announce Type: cross Abstract: This paper presents a unified system designed to support precision agriculture by integrating advanced weather prediction, crop recommendation, and a

Cross-LLM Consistency in Inference: Evidence from Shared Interactions

arXiv:2606.08129v1 Announce Type: new Abstract: Large language models (LLMs) differ in architecture, training data, and optimization procedures, yet they may still develop similar internal inference p

Cryptographic Backdoor for Neural Networks: Boon and Bane

arXiv:2509.20714v2 Announce Type: replace-cross Abstract: In this paper we show that cryptographic backdoors in a neural network (NN) can be highly effective in two directions, namely mounting the att

Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning

arXiv:2606.08311v1 Announce Type: new Abstract: Electronic health record (EHR) notes are dense medical documents containing large amounts of information, often filled with complex medical jargon. High

DALE-CT: Depth-Aware Foundation Models for Computed Tomography

arXiv:2606.07775v1 Announce Type: new Abstract: Recent breakthroughs in self-supervised learning (SSL), such as the Latent-Euclidean Joint-Embedding Predictive Architecture (LeJEPA), alongside success

Data augmented bootstrap: Unifying confidence interval construction by approximate invariance

arXiv:2606.09049v1 Announce Type: cross Abstract: We propose the data augmented bootstrap (DAB), a framework for constructing confidence intervals from approximately invariant transformations of the d

Data-driven discovery of governing differential equations across physical systems

arXiv:2606.09638v1 Announce Type: new Abstract: Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical

Dealing with Annotator Disagreement in Hate Speech Classification

arXiv:2502.08266v3 Announce Type: replace-cross Abstract: Hate speech detection is a crucial task, especially on social media where harmful content can spread quickly. Collecting social media content

Decentralized Online Riemannian Optimization Beyond Hadamard Manifolds

arXiv:2509.07779v2 Announce Type: replace-cross Abstract: We study decentralized online Riemannian optimization over manifolds with possibly positive curvature, going beyond the Hadamard manifold sett

Decision-Focused Continual Learning for Seaport Power-Logistics Scheduling: Generalization across Varying Tasks

arXiv:2511.07938v3 Announce Type: replace Abstract: Power-logistics scheduling in modern seaports typically follows a predict-then-optimize pipeline. To enhance the decision quality of predictions, de

Decoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework

arXiv:2606.07707v1 Announce Type: new Abstract: Decoding emotional states from neural signals has been typically framed as a discrete, single-label classification task based on emotionally stable stim

Decoupling the 'What' and 'Where' With Polar Coordinate Positional Embeddings

arXiv:2509.10534v3 Announce Type: replace-cross Abstract: The attention mechanism in a Transformer architecture matches key to query based on both content -- the what -- and position in a sequence --

Decoy-Calibrated Failure Audits for Language Models

arXiv:2606.09046v1 Announce Type: new Abstract: Useful audits reveal not only how often a model fails, but also where its failures concentrate. An auditor may test many candidate explanations: long in

Deep Active Re-Labeling: Toward Noise-Resilient Annotation Efficiency

arXiv:2606.08718v1 Announce Type: cross Abstract: While Deep Active Learning (DAL) effectively reduces human annotation costs, its efficacy is constrained by human annotation errors. This is because t

Dense Force Estimation with an Event-based Optical Tactile Sensor

arXiv:2606.09451v1 Announce Type: cross Abstract: Humans rely on spatially dense, geometry and force-aware tactile feedback at high temporal resolution for dexterous manipulation. While vision-based t

Deterministic Execution of ROS~2 Applications via Lingua Franca

arXiv:2606.09203v1 Announce Type: new Abstract: The Robot Operating System~2 (ROS 2) is a widely used middleware for robotic systems, characterized by a publish-subscribe (pub-sub) communication mecha

researcharxiv-cs-ro

Differentially Private Range Subgraph Counting

arXiv:2606.08179v1 Announce Type: cross Abstract: Subgraph counting is a fundamental problem in graph analysis. Motivated by practical scenarios where graph analytics are performed on subgraphs induce

DifferSeg: Towards Diverse Multimodal Binary Segmentation via Differential Perception and Frequency Guidance

arXiv:2606.08906v1 Announce Type: new Abstract: In many binary segmentation tasks, most multimodal methods rely on fixed feature concatenation for cross-modal interaction and straightforward decoder d

DiffoR: A Unified Continuous Generative Framework for Universal Ordinal Regression

arXiv:2606.07599v1 Announce Type: cross Abstract: Ordinal Regression (OR) aims to predict target values with inherent order, underpinning critical applications across diverse domains, from recommender

DiffSight-Former: Modeling Structural Differences and Temporal Dynamics for Glaucoma Progression Prediction

arXiv:2606.09140v1 Announce Type: new Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, and early detection from fundus images is critical for effective disease management. Wh

Safety

Diffuse AI Control on Fuzzy Tasks

arXiv:2606.08892v1 Announce Type: new Abstract: AI models deployed in critical domains, such as AI safety research, may subtly sabotage our efforts due to misalignment. Diffuse AI Control is a subfiel

safetyarxiv-cs-lg

Diffusion Bridge or Flow Matching? A Unifying Framework and Comparative Analysis

arXiv:2509.24531v2 Announce Type: replace Abstract: Diffusion Bridge and Flow Matching have both demonstrated compelling empirical performance in transformation between arbitrary distributions. Howeve

Discovering Expert-Level Nash Equilibrium Algorithms with Large Language Models

arXiv:2508.11874v2 Announce Type: replace-cross Abstract: Designing polynomial-time algorithms for approximate Nash equilibria (ANE) with provable worst-case guarantees is a fundamental open problem i

Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model

arXiv:2606.09770v1 Announce Type: cross Abstract: Nearby neurons in cortex share similar response profiles, producing systematic spatial organization across sensory and cognitive systems. Recent topog

Disentangled Feature Importance

arXiv:2507.00260v3 Announce Type: replace-cross Abstract: When predictors are statistically dependent, the appropriate definition of feature importance depends on the operational goal. Conditional-inc

Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference

arXiv:2606.07677v1 Announce Type: cross Abstract: Electronic health records (EHR) pose large-scale multi-disease modeling problems in which many outcomes are rare and strongly influenced by shared ris

Disjoint Generation of Synthetic Data

arXiv:2507.19700v2 Announce Type: replace Abstract: We propose a new framework for generating tabular synthetic datasets via disjoint generative models. In this paradigm, a dataset is partitioned into

Do Video Foundation Models Understand Intuitive Physics? A Layerwise Probing Analysis

arXiv:2606.09646v1 Announce Type: cross Abstract: We study whether pretrained video foundation models encode intuitive-physics information in their frozen representations, and how this information var

DynaCF: Mitigating Shortcut Learning in Reward Models via Dynamic Counterfactual Sensitivity

arXiv:2606.09043v1 Announce Type: new Abstract: Reward models trained from pairwise preferences often exploit superficial shortcut cues rather than learning true response quality. We propose DynaCF, a

Echo-Memory: A Controlled Study of Memory in Action World Models

arXiv:2606.09803v1 Announce Type: new Abstract: We present extbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models. These models generate multi-segment videos fr

Edge-Constrained UAV Small-Object Detection with P2 Enhancement and Quantum-Inspired Lightweight Structure Search

arXiv:2606.09081v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) object detection requires compact detectors that retain small-object details under onboard computation and memory constrai

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization

arXiv:2510.10028v2 Announce Type: replace-cross Abstract: The rapid advancement of Low-Altitude Economy Networks (LAENets) has enabled a variety of applications, including aerial surveillance, environ

EgoPriMo: Egocentric Motion Generation for Interactive Humanoid Control

arXiv:2606.08495v1 Announce Type: cross Abstract: Humanoid robots require whole-body motions that adapt to scene context, task requirements, and user intent. Motion tracking reproduces specified traje

EinSort: Sorting is All We Need for Tensorizing LLM

arXiv:2606.08565v1 Announce Type: cross Abstract: Tensor networks provide efficient representations for compressing large neural networks. By carefully designing shapes and topologies, they can signif

Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs

arXiv:2406.07318v3 Announce Type: replace Abstract: The utilisation of event cameras represents an important and swiftly evolving trend aimed at addressing the constraints of traditional video systems

Emergence via Phase Transitions: Mechanism Landscapes and Universal Convergence Across Complex Systems

arXiv:2606.07563v1 Announce Type: cross Abstract: Across machine learning, biology, and physics, independently evolving systems often converge toward strikingly similar high-level structures despite r

Enabling KV Caching of Shared Prefix for Diffusion Language Models

arXiv:2606.07571v1 Announce Type: cross Abstract: Key-value (KV) caching for shared prefixes is essential for high-throughput large language model (LLM) serving, but it faces critical challenges in em

End-to-End Control of a Powered Knee-Ankle Prosthesis Towards Unified, Tuning-Free Assistance

arXiv:2606.07902v1 Announce Type: new Abstract: Powered prostheses conventionally rely on impedance controllers that require extensive manual tuning and explicit mode classification. In this work, we

researcharxiv-cs-ro

End-to-End Optimization of Incoherent Imaging for Classification Under Detector-Limited Readout

arXiv:2606.09792v1 Announce Type: new Abstract: End-to-end co-optimization of optical front-ends (e.g. metasurfaces) and neural network back-ends has been widely applied to imaging tasks, yet a formal

ePC: Fast and Deep Predictive Coding in Digital Simulation

arXiv:2505.20137v5 Announce Type: replace-cross Abstract: Predictive Coding (PC) offers a brain-inspired alternative to backpropagation for neural network training, described as a physical system mini

EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation

arXiv:2606.08980v1 Announce Type: new Abstract: This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic segmentation. Unlike existing methods relying on ad

Estimate Collapsibility of Causal Effects in Completed Partial DAGs via Strong d-Convex Hulls

arXiv:2606.08941v1 Announce Type: cross Abstract: This paper proposes a collapsible method for estimating causal effects that maintains the estimator's consistency before and after marginalization ove

Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles

arXiv:2606.09718v1 Announce Type: cross Abstract: Diffusion models have demonstrated remarkable generative capabilities and have also emerged as powerful self-supervised representation learners, yet t

EvoCSFL: Surrogate-Assisted Evolutionary Client Selection for Efficient and Robust Federated Learning

arXiv:2606.07702v1 Announce Type: cross Abstract: The heterogeneity of client data and systems makes it difficult to achieve satisfactory convergence speed and robustness in federated learning with ra