Search: “research”

Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification

arXiv:2603.29148v2 Announce Type: replace-cross Abstract: Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for larg

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Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects

DGX agent

arXiv:2604.05546v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency

researcharxiv-cs-cl

15 Apr 2026

Efficient Semantic Image Communication for Traffic Monitoring at the Edge

arXiv:2604.12622v1 Announce Type: cross Abstract: Many visual monitoring systems operate under strict communication constraints, where transmitting full-resolution images is impractical and often unne

Elastic Net Regularization and Gabor Dictionary for Classification of Heart Sound Signals using Deep Learning

arXiv:2604.12483v1 Announce Type: cross Abstract: In this article, we propose the optimization of the resolution of time-frequency atoms and the regularization of fitting models to obtain better repre

Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database

arXiv:2512.21652v2 Announce Type: replace-cross Abstract: Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD)

Enhance-then-Balance Modality Collaboration for Robust Multimodal Sentiment Analysis

arXiv:2604.12518v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) integrates heterogeneous text, audio, and visual signals to infer human emotions. While recent approaches leverage c

Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning

arXiv:2505.19261v2 Announce Type: replace-cross Abstract: Current text-to-image diffusion generation typically employs complete-text conditioning. Due to the intricate syntax, diffusion transformers (

Exploring Concept Subspace for Self-explainable Text-Attributed Graph Learning

arXiv:2604.11986v1 Announce Type: new Abstract: We introduce Graph Concept Bottleneck (GCB) as a new paradigm for self-explainable text-attributed graph learning. GCB maps graphs into a subspace, conc

Fall Risk and Gait Analysis in Community-Dwelling Older Adults using World-Spaced 3D Human Mesh Recovery

arXiv:2604.11961v1 Announce Type: new Abstract: Gait assessment is a key clinical indicator of fall risk and overall health in older adults. However, standard clinical practice is largely limited to s

Free Random Projection for In-Context Reinforcement Learning

arXiv:2504.06983v3 Announce Type: replace Abstract: Hierarchical inductive biases are hypothesized to promote generalizable policies in reinforcement learning, as demonstrated by explicit hyperbolic l

From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception

arXiv:2604.12508v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine

From edges to meaning: Semantic line sketches as a cognitive scaffold for ancient pictograph invention

arXiv:2604.12865v1 Announce Type: new Abstract: Humans readily recognize objects from sparse line drawings, a capacity that appears early in development and persists across cultures, suggesting neural

From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution

arXiv:2604.12474v1 Announce Type: cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission. Such problems are inherently mixed discrete-continuou

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix

arXiv:2510.06685v2 Announce Type: replace-cross Abstract: Self-attention layers have become fundamental building blocks of modern deep neural networks, yet their theoretical understanding remains limi

Generative Modeling Enables Molecular Structure Retrieval from Coulomb Explosion Imaging

arXiv:2511.00179v2 Announce Type: replace-cross Abstract: Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essen

GeoPl@ntNet: A Platform for Exploring Essential Biodiversity Variables

arXiv:2511.13790v2 Announce Type: replace-cross Abstract: This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandab

HiFiNet: Hierarchical Fault Identification in Wireless Sensor Networks via Edge-Based Classification and Graph Aggregation

arXiv:2511.17537v2 Announce Type: replace-cross Abstract: Wireless Sensor Networks (WSN) are the backbone of essential monitoring applications, but their deployment in unfavourable conditions increase

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models

arXiv:2604.12115v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal performance, but still suffer from hallucinations caused by unstable visual grounding and

Human-Inspired Context-Selective Multimodal Memory for Social Robots

arXiv:2604.12081v1 Announce Type: new Abstract: Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the con

Hypergraph-State Collaborative Reasoning for Multi-Object Tracking

arXiv:2604.12665v1 Announce Type: new Abstract: Motion reasoning serves as the cornerstone of multi-object tracking (MOT), as it enables consistent association of targets across frames. However, exist

IMU: Influence-guided Machine Unlearning

arXiv:2508.01620v3 Announce Type: replace-cross Abstract: Machine Unlearning (MU) aims to selectively erase the influence of specific data points from pretrained models. However, most existing MU meth

Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging

arXiv:2604.12709v1 Announce Type: cross Abstract: Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with sign

Interpretable DNA Sequence Classification via Dynamic Feature Generation in Decision Trees

arXiv:2604.12060v1 Announce Type: cross Abstract: The analysis of DNA sequences has become critical in numerous fields, from evolutionary biology to understanding gene regulation and disease mechanism

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

JanusCoder: Towards a Foundational Visual-Programmatic Interface for Code Intelligence

arXiv:2510.23538v2 Announce Type: replace Abstract: The scope of neural code intelligence is rapidly expanding beyond text-based source code to encompass the rich visual outputs that programs generate

Joint Multi-Target Detection-Tracking in Cognitive Massive MIMO Radar via POMCP

arXiv:2507.17506v3 Announce Type: replace-cross Abstract: This work presents a cognitive radar (CR) framework to enhance remote sensing performance, specifically focusing on tracking multiple targets

KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning

arXiv:2604.12487v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit strong abilities in natural language understanding and generation, yet they struggle with knowledge-intensive rea

Latent-Condensed Transformer for Efficient Long Context Modeling

arXiv:2604.12452v1 Announce Type: new Abstract: Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic

Latent patterns of urban mixing in mobility analysis across five global cities

arXiv:2604.12202v1 Announce Type: new Abstract: This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individua

Learned Incremental Nonlinear Dynamic Inversion for Quadrotors with and without Slung Payloads

arXiv:2503.09441v2 Announce Type: replace Abstract: The increasing complexity of multirotor applications demands flight controllers that can accurately account for all forces acting on the vehicle. Co

researcharxiv-cs-ro

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

Learning to accelerate distributed ADMM using graph neural networks

arXiv:2509.05288v2 Announce Type: replace Abstract: Distributed optimization is fundamental to large-scale machine learning and control applications. Among existing methods, the alternating direction

LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability

arXiv:2510.03174v2 Announce Type: replace-cross Abstract: Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topi

Loop Corrections to the Training and Generalization Errors of Random Feature Models

arXiv:2604.12827v1 Announce Type: cross Abstract: We investigate random feature models in which neural networks sampled from a prescribed initialization ensemble are frozen and used as random features

LoSA: Locality Aware Sparse Attention for Block-Wise Diffusion Language Models

arXiv:2604.12056v1 Announce Type: new Abstract: Block-wise diffusion language models (DLMs) generate multiple tokens in any order, offering a promising alternative to the autoregressive decoding pipel

Loss-Driven Bayesian Active Learning

arXiv:2604.11995v1 Announce Type: new Abstract: The central goal of active learning is to gather data that maximises downstream predictive performance, but popular approaches have limited flexibility

Lyra 2.0: Explorable Generative 3D Worlds

arXiv:2604.13036v1 Announce Type: new Abstract: Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, t

Machine Learning-Based Real-Time Detection of Compensatory Trunk Movements Using Trunk-Wrist Inertial Measurement Units

arXiv:2604.12591v1 Announce Type: new Abstract: Compensatory trunk movements (CTMs) are commonly observed after stroke and can lead to maladaptive movement patterns, limiting targeted training of affe

researcharxiv-cs-ro

Machine learning for four-dimensional SU(3) lattice gauge theories

arXiv:2604.12416v1 Announce Type: cross Abstract: In this review I summarize how machine learning can be used in lattice gauge theory simulations and what ap-proaches are currently available to improv

MAML-KT: Addressing Cold Start Problem in Knowledge Tracing for New Students via Few-Shot Model-Agnostic Meta Learning

arXiv:2603.00137v2 Announce Type: replace-cross Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. While

MAST: Mask-Guided Attention Mass Allocation for Training-Free Multi-Style Transfer

arXiv:2604.12281v1 Announce Type: cross Abstract: Style transfer aims to render a content image with the visual characteristics of a reference style while preserving its underlying semantic layout and

MetFuse: Figurative Fusion between Metonymy and Metaphor

arXiv:2604.12919v1 Announce Type: new Abstract: Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that tr

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

arXiv:2603.19796v3 Announce Type: replace-cross Abstract: Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete na

researcharxiv-cs-ro

MultiDocFusion: Hierarchical and Multimodal Chunking Pipeline for Enhanced RAG on Long Industrial Documents

arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging

arXiv:2505.23209v3 Announce Type: replace Abstract: Model merging has emerged as an efficient method to combine multiple single-task fine-tuned models. The merged model can enjoy multi-task capabiliti

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

On the Convergence Analysis of Muon

arXiv:2505.23737v2 Announce Type: replace-cross Abstract: The majority of parameters in neural networks are naturally represented as matrices. However, most commonly used optimizers treat these matrix

One Token Away from Collapse: The Fragility of Instruction-Tuned Helpfulness

arXiv:2604.13006v1 Announce Type: cross Abstract: Instruction-tuned large language models produce helpful, structured responses, but how robust is this helpfulness when trivially constrained? We show