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arXiv:2602.19328v1 Announce Type: new Abstract: In recent years extensions of manifold Ricci curvature to discrete combinatorial objects such as graphs and hypergraphs (popularly called as...
arXiv:2602.19330v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are increasingly explored for physical design analysis in Electronic Design Automation, particularly for modeling Clock Tree...
arXiv:2602.19331v1 Announce Type: new Abstract: Representational similarity metrics typically force all units to be matched, making them susceptible to noise and outliers common in neural...
arXiv:2602.19332v1 Announce Type: new Abstract: Model merging has emerged as a powerful paradigm for combining the capabilities of distinct expert models without the high computational...
arXiv:2602.19333v1 Announce Type: new Abstract: This research introduces the first large-scale, well-balanced Persian social media text classification dataset, specifically designed to address the lack of...
arXiv:2602.19338v1 Announce Type: new Abstract: The increasing variety of input data and complexity of tasks that are handled by the devices of internet of things...
arXiv:2602.19339v1 Announce Type: new Abstract: Offline evaluation of recommender systems is often affected by hidden, under-documented choices in data preparation. Seemingly minor decisions in filtering,...
arXiv:2602.19341v1 Announce Type: new Abstract: The emergence of Autonomous Mobility-on-Demand (AMoD) services creates new opportunities to improve the efficiency and reliability of on-demand mobility systems....
arXiv:2602.19345v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has significantly advanced the training of large language models and enhanced their reasoning capabilities, while...
arXiv:2602.19346v1 Announce Type: new Abstract: Modular small-scale robots offer the potential for on-demand assembly and disassembly, enabling task-specific adaptation in dynamic and constrained environments. However,...
arXiv:2602.19348v1 Announce Type: new Abstract: Acquiring aligned visuo-tactile datasets is slow and costly, requiring specialised hardware and large-scale data collection. Synthetic generation is promising, but...
arXiv:2602.19349v1 Announce Type: new Abstract: LiDAR-camera fusion enhances 3D panoptic segmentation by leveraging camera images to complement sparse LiDAR scans, but it also introduces a...
arXiv:2602.19350v1 Announce Type: new Abstract: Digitizing humans and synthesizing photorealistic avatars with explicit 3D pose and camera controls are central to VR, telepresence, and entertainment....
arXiv:2602.19352v1 Announce Type: new Abstract: Despite having growing awareness and concerns about privacy, technology users are often insufficiently informed of the data practices of various...
arXiv:2602.19353v1 Announce Type: new Abstract: Research Software Engineers (RSEs) have become indispensable to computational research and scholarship. The fast rise of RSEs in higher education...
arXiv:2602.19354v1 Announce Type: new Abstract: Lightweight fine-tuning techniques and the rise of 'open' AI model marketplaces have enabled individuals to easily build and release generative...
arXiv:2602.19355v1 Announce Type: new Abstract: Generalization is often regarded as an essential property of machine learning systems. However, perhaps not every component of a system...
arXiv:2602.19357v1 Announce Type: new Abstract: Spatial visualization is the mental ability to imagine, transform, and manipulate the spatial characteristics of objects and actions. This intelligence...
arXiv:2602.19358v1 Announce Type: new Abstract: Precise, object-aware control over visual content is essential for advanced image editing and compositional generation. Yet, most existing approaches operate...
arXiv:2602.19359v1 Announce Type: new Abstract: Calibrating a robot simulator's physics parameters (friction, damping, material stiffness) to match real hardware is often done by hand or...
arXiv:2602.19360v1 Announce Type: new Abstract: Federated data processing (FDP) offers a promising approach for enabling collaborative analysis of sensitive data without centralizing raw datasets. However,...
arXiv:2602.19362v1 Announce Type: new Abstract: Reinforcement learning (RL) approaches for Large Language Models (LLMs) frequently use on-policy algorithms, such as PPO or GRPO. However, policy...
arXiv:2602.19366v1 Announce Type: new Abstract: We study how to scale distributed bandit submodular coordination under realistic communication constraints in bandwidth, data rate, and connectivity. We...
arXiv:2602.19367v1 Announce Type: new Abstract: The Platonic Representation Hypothesis posits that learned representations from models trained on different modalities converge to a shared latent structure...