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arXiv:2603.00587v1 Announce Type: new Abstract: Evaluating machine unlearning remains challenging, as existing methods typically require retraining reference models or performing membership inference attacks, both of...
arXiv:2603.00588v1 Announce Type: new Abstract: Efficient representation learning is essential for optimal information storage and classification. However, it is frequently overlooked in artificial neural networks...
arXiv:2603.00590v1 Announce Type: new Abstract: As artificial intelligence (AI) is increasingly deployed across domains, ensuring fairness has become a core challenge. However, the field faces...
arXiv:2603.00592v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models achieve over 95% success on standard benchmarks. However, through systematic experiments, we find that current state-of-the-art VLA...
arXiv:2603.00594v1 Announce Type: new Abstract: In this paper, we consider the integrating factor midpoint method for wave-type equations and derive optimal order a posteriori error...
arXiv:2603.00595v1 Announce Type: new Abstract: Counting is a core capability for multimodal large language models (MLLMs), yet there is no unified counting dataset to rigorously...
arXiv:2603.00597v1 Announce Type: new Abstract: Inertial Odometry (IO) has gained attention in quadrotor applications due to its sole reliance on inertial measurement units (IMUs), attributed...
arXiv:2603.00598v1 Announce Type: new Abstract: Research in Human-Computer Interaction (HCI) has shown that caring for others, including both humans (e.g., close friends) and computers (e.g.,...
arXiv:2603.00599v1 Announce Type: new Abstract: Hypergraphs are the natural description of higher-order interactions among objects, widely applied in social network analysis, cross-modal retrieval, etc. Hypergraph...
arXiv:2603.00600v1 Announce Type: new Abstract: Active perception, the ability of a robot to proactively adjust its viewpoint to acquire task-relevant information, is essential for robust...
arXiv:2603.00601v1 Announce Type: new Abstract: AI code agents excel at isolated tasks yet struggle with complex, multi-file software engineering requiring understanding of how dozens of...
arXiv:2603.00602v1 Announce Type: new Abstract: Detecting out-of-distribution (OOD) graphs is crucial for ensuring the safety and reliability of Graph Neural Networks. In unsupervised graph-level OOD...
arXiv:2603.00604v1 Announce Type: new Abstract: High-quality pixel-level annotations are essential for the semantic segmentation of remote sensing imagery. However, such labels are expensive to obtain...
arXiv:2603.00606v1 Announce Type: new Abstract: Accurate 3D hand pose and pressure sensing is essential for immersive human-computer interaction, yet simultaneously achieving both in mobile scenarios...
arXiv:2603.00607v1 Announce Type: new Abstract: Multi-subject image generation requires seamlessly harmonizing multiple reference identities within a coherent scene. However, existing methods relying on rigid spatial...
arXiv:2603.00608v1 Announce Type: new Abstract: Student repetition in secondary education imposes significant resource burdens, particularly in resource-constrained contexts. Addressing this challenge, this study introduces a...
arXiv:2603.00609v1 Announce Type: new Abstract: Collaborative perception leverages data exchange among multiple agents to enhance overall perception capabilities. However, heterogeneity across agents introduces domain gaps...
arXiv:2603.00610v1 Announce Type: new Abstract: While music generation models have evolved to handle complex multimodal inputs mixing text, lyrics, and reference audio, evaluation mechanisms have...
arXiv:2603.00611v1 Announce Type: new Abstract: Recently, Spectral Compressive Imaging (SCI) has achieved remarkable success, unlocking significant potential for dynamic spectral vision. However, existing reconstruction methods,...
arXiv:2603.00612v1 Announce Type: new Abstract: The rapid growth of biomedical literature and curated databases has made it increasingly difficult for researchers to systematically connect biomarker...
arXiv:2603.00615v1 Announce Type: new Abstract: The performance of robotic imitation learning is fundamentally limited by data quality and training strategies. Prevalent sampling strategies on RLBench...
arXiv:2603.00616v1 Announce Type: new Abstract: Modern cyber-physical systems, such as automotive control, rely on feedback controllers that regulate the system towards desired a setpoint. In...
arXiv:2603.00617v1 Announce Type: new Abstract: The persistent militarization of large reasoning models stems not from technical necessity but from governance arrangements that strip researchers of...
arXiv:2603.00618v1 Announce Type: new Abstract: Multi-domain graph pre-training integrates knowledge from diverse domains to enhance performance in the target domains, which is crucial for building...