Knowledge catalogue
arXiv:2607.07277v1 Announce Type: new Abstract: Harmful online communication often contains slang, coded terms, abbreviations, and community-specific expressions, which make messages difficult to inte
arXiv:2607.06807v1 Announce Type: cross Abstract: While enabling effective collaboration on complex tasks, LLM-based Multi-Agent Systems (MAS) face critical security challenges due to vulnerabilities
arXiv:2607.06634v1 Announce Type: new Abstract: Compact networks built from Clifford algebra Cl(3,0) primitives are exactly SO(3)-equivariant and learn synthetic 3D vector laws from few samples. We as
arXiv:2210.16286v2 Announce Type: replace Abstract: To understand the training dynamics of neural networks, prior studies have considered the mean-field limit of two-layer neural networks as the width
arXiv:2607.05467v1 Announce Type: new Abstract: Fog severely degrades the visibility of small unmanned aerial vehicles (UAVs) in skydominant, long-range imagery, reducing the reliability of downstream
arXiv:2607.05708v1 Announce Type: new Abstract: Recent LLM-based agent systems continuously accumulate context across multi-turn interactions, tool invocations, and cross-session workflows. Replaying
arXiv:2607.05733v1 Announce Type: new Abstract: Generating temporally continuous and socially coherent human motion from text remains a fundamental challenge, particularly in realistic streams where p
arXiv:2607.06484v1 Announce Type: cross Abstract: Poisoning attacks against public datasets lead to major concerns, such as (i) misclassification of perceived objects when the poisoned data is used fo
arXiv:2606.14948v2 Announce Type: replace-cross Abstract: LLMs have substantially improved software engineering yet real-world development requires architectural understanding. Such understanding is p
arXiv:2511.16137v2 Announce Type: replace Abstract: Existing studies on quality enhancement for compressed video (QECV) predominantly rely on known quantization parameters (QPs), training separate enh
arXiv:2607.05850v1 Announce Type: new Abstract: Deep neural networks trained with Empirical Risk Minimization (ERM) often fail under distribution shifts because they exploit spurious correlations betw
arXiv:2607.05419v1 Announce Type: cross Abstract: Accurate and timely channel state information (CSI) is essential for next-generation wireless systems, yet existing works treat CSI compression and CS
arXiv:2607.05625v1 Announce Type: new Abstract: Wound monitoring is a critical yet underserved clinical challenge, where timely identification of severe adverse events (SAEs) such as infection, tissue
arXiv:2607.05787v1 Announce Type: new Abstract: Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. A
arXiv:2607.05883v1 Announce Type: new Abstract: In dual-arm dexterous teleoperation, cross-platform generalization of motion retargeting and interactivity of grasping are crucial. However, the heterog
arXiv:2603.19216v2 Announce Type: replace-cross Abstract: Understanding and generating 3D objects as compositions of meaningful parts is fundamental to human perception and reasoning. However, most te
arXiv:2607.06217v1 Announce Type: new Abstract: Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficie
arXiv:2607.05559v1 Announce Type: new Abstract: Foundation machine learning force fields (MLFFs) such as MACE-MP-0 and UMA cover broad chemical space at near density functional theory (DFT) accuracy.
arXiv:2602.10710v2 Announce Type: replace Abstract: With the increasing availability of high-resolution remote sensing and aerial imagery, oriented object detection has become a key capability for geo
arXiv:2607.05758v1 Announce Type: cross Abstract: Automated experimentation is moving from closed-loop optimization toward open decision-making, where human or AI planners must forecast the consequenc
arXiv:2504.16595v2 Announce Type: replace-cross Abstract: Packing objects efficiently is a fundamental problem in logistics, warehouse automation, and robotics. When dealing with highly diverse 3D obj
arXiv:2607.05585v1 Announce Type: cross Abstract: FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosi
arXiv:2607.06268v1 Announce Type: new Abstract: Multi-view reasoning in coronary X-ray angiography is inherently a cross-projection geometric problem, yet automated report generation in this setting r
arXiv:2607.05438v1 Announce Type: cross Abstract: Multimodal retrieval-augmented generation (RAG) grounds a generator in evidence drawn from heterogeneous modalities -- text, tables, and images. The d
arXiv:2607.06083v1 Announce Type: new Abstract: Existing deep learning methods perform well in medical image classification but struggle with multi-scale morphology and limited annotations due to fixe
arXiv:2603.12144v2 Announce Type: replace Abstract: Understanding and reconstructing the 3D world through omnidirectional perception is becoming increasingly important for autonomous agents and embodi
arXiv:2607.05663v1 Announce Type: cross Abstract: Accurate and robust localization is essential for autonomous mobility systems in real-world environments. While fusing Inertial Measurement Unit (IMU)
arXiv:2607.05911v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to combine known attributes and objects as primitives for recognizing previously unseen attribute-object pa
Provisioned Throughput is a new serverless product from @togethercompute w/ guaranteed TPMs. We created this for mission critical enterprise class applications. It functions like dedicated capacity bu
arXiv:2607.06097v1 Announce Type: cross Abstract: 3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive
arXiv:2607.05837v1 Announce Type: new Abstract: Defocus blur degrades fine image structures and limits visual perception, which can adversely affect downstream vision tasks. Although recent deep learn
arXiv:2607.06109v1 Announce Type: cross Abstract: Multi-perturbation adversarial training (MAT) aims to achieve robustness against multiple ell_p perturbations but suffers from robustness trade-offs b
arXiv:2607.06026v1 Announce Type: new Abstract: We present a novel isogeometric deep learning method, termed SplineNet, for the seamless design and analysis of shell structures with complex geometries
arXiv:2607.06356v1 Announce Type: cross Abstract: Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri
arXiv:2607.05609v1 Announce Type: cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, of
arXiv:2607.06349v1 Announce Type: new Abstract: Building sensors are embedded in physical topology, spatial hierarchy, and operational context, yet existing forecasters often treat them as isolated ti
arXiv:2410.11378v3 Announce Type: replace-cross Abstract: Personalized collaborative learning in federated settings faces a critical trade-off between customization and participant trust. Existing app
arXiv:2607.06549v1 Announce Type: new Abstract: Deep learning-based computer-aided diagnosis (CAD) systems have shown strong performance in breast cancer diagnosis, particularly for classification tas
arXiv:2606.12502v2 Announce Type: replace-cross Abstract: We propose that value -- the quantity goal-directed agents create, destroy, and exchange -- is a lawful structural quantity in the same catego
arXiv:2204.02803v2 Announce Type: replace-cross Abstract: Sign language recognition from monocular video or 2D pose sequences is challenging, both because 3D information must be inferred from 2D obser
arXiv:2607.02572v1 Announce Type: cross Abstract: In multi-source image fusion scenarios, heterogeneous inputs are typically driven by distinct generative mechanisms and can be viewed as a composition
arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel
arXiv:2607.05292v1 Announce Type: cross Abstract: Super-resolving coarse atmospheric fields to local PM_{2.5} variations is uniquely challenged by a mismatch in spatial support: while pixels represent
arXiv:2607.02699v1 Announce Type: new Abstract: The object detection in satellite imagery has garnered considerable attention due to its extensive real-world applications and the inherent challenges i
arXiv:2607.05205v1 Announce Type: new Abstract: Fast and reliable motion detection is essential for machine vision and autonomous systems operating in dynamic environments. This work integrates emergi
arXiv:2607.04311v1 Announce Type: new Abstract: Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity
arXiv:2607.03936v1 Announce Type: new Abstract: A key challenge in Arabic NLP is the scarcity of dialectal data relative to Modern Standard Arabic (MSA), causing LLMs to overproduce MSA and struggle w
arXiv:2607.03466v1 Announce Type: cross Abstract: This study aims to predict Tumor, Node, and Metastasis (TNM) stage labels independently, with the Cancer Genome Atlas (TCGA) pathology report as the s
arXiv:2607.05204v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade im
arXiv:2606.15198v2 Announce Type: replace Abstract: City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied
arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m
arXiv:2607.04940v1 Announce Type: new Abstract: Human-like dexterous hands with multiple fingers offer human-level manipulation capabilities but remain difficult to train the control policies that can
arXiv:2607.02746v1 Announce Type: cross Abstract: Machine learning has shown speedups for numerical methods in physics applications, but integrating Python-based libraries into high-performance C++ so
arXiv:2607.02928v1 Announce Type: new Abstract: Cold-start drug-drug interaction (DDI) prediction for new drugs is critical for minimizing unexpected adverse drug reactions. The key challenge is to ca
arXiv:2607.03853v1 Announce Type: new Abstract: Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no
arXiv:2607.04800v1 Announce Type: new Abstract: Neural networks are thought to represent concepts as directions in their activation space, and superposition lets them encode more concepts than they ha
arXiv:2607.02799v1 Announce Type: new Abstract: Large-scale dyadic interactive audio-visual dialogue (DIAD) datasets provide fundamental data resources for developing humanoid interactive virtual agen
arXiv:2607.03557v1 Announce Type: new Abstract: While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under
arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio
arXiv:2603.14830v3 Announce Type: replace Abstract: Dataset distillation, a training-aware data compression technique, has recently attracted increasing attention as an effective tool for mitigating c