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arXiv:2602.19313v1 Announce Type: new Abstract: While Vision-Language-Action (VLA) models have seen rapid progress in pretraining, their advancement in Reinforcement Learning (RL) remains hampered by low...
arXiv:2602.19314v1 Announce Type: new Abstract: The image purification strategy constructs an intermediate distribution with aligned anatomical structures, which effectively corrects the spatial misalignment between real-world...
arXiv:2602.19316v1 Announce Type: new Abstract: Unified Speech Recognition (USR) has emerged as a semi-supervised framework for training a single model for audio, visual, and audiovisual...
arXiv:2602.19317v1 Announce Type: new Abstract: Personalization in Question Answering (QA) requires answers that are both accurate and aligned with users' background, preferences, and historical context....
arXiv:2602.19319v1 Announce Type: new Abstract: Managing personal health data is a challenge in today's fragmented and institution-centric healthcare ecosystem. Individuals often lack meaningful control over...
arXiv:2602.19320v1 Announce Type: new Abstract: Agentic memory systems enable large language model (LLM) agents to maintain state across long interactions, supporting long-horizon reasoning and personalization...
arXiv:2602.19322v1 Announce Type: new Abstract: Ultrasound (US) imaging poses unique challenges for representation learning due to its inherently noisy acquisition process. The low signal-to-noise ratio...
arXiv:2602.19323v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However,...
arXiv:2602.19324v1 Announce Type: new Abstract: Early and accurate classification of retinal diseases is critical to counter vision loss and for guiding clinical management of retinal...
arXiv:2602.19326v1 Announce Type: new Abstract: As cities evolve over time, challenges such as traffic congestion and functional imbalance increasingly necessitate urban renewal through efficient modification...
arXiv:2602.19327v1 Announce Type: new Abstract: A significant portion of recent research on Large Language Model (LLM) alignment focuses on developing new policy optimization methods based...
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....