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arXiv:2603.04767v1 Announce Type: new Abstract: Conditional time series generation plays a critical role in addressing data scarcity and enabling causal analysis in real-world applications. Despite …
arXiv:2603.04768v1 Announce Type: new Abstract: Equalizer parameter optimization is critical for signal integrity in high-speed memory systems operating at multi-gigabit data rates. However, existing methods …
arXiv:2603.04780v1 Announce Type: new Abstract: Causal discovery with latent variables is a fundamental task. Yet most existing methods rely on strong structural assumptions, such as …
arXiv:2603.04790v1 Announce Type: new Abstract: Reinforcement learning (RL) has been extensively employed in a wide range of decision-making problems, such as games and robotics. Recently, …
arXiv:2603.04827v1 Announce Type: new Abstract: Algorithmic speedup of training common neural architectures is made difficult by the lack of structure guaranteed by the function compositions …
arXiv:2603.04831v1 Announce Type: new Abstract: Popular explanation methods often produce unreliable feature importance scores due to missingness bias, a systematic distortion that arises when models …
arXiv:2603.04851v1 Announce Type: new Abstract: Why is safety alignment in LLMs shallow? We prove that gradient-based alignment inherently concentrates on positions where harm is decided …
arXiv:2603.04881v1 Announce Type: new Abstract: Differentially private learning is essential for training models on sensitive data, but empirical studies consistently show that it can degrade …
arXiv:2603.04890v1 Announce Type: new Abstract: Multimodal Federated Learning (MFL) enables clients with heterogeneous data modalities to collaboratively train models without sharing raw data, offering a …
arXiv:2603.04898v1 Announce Type: new Abstract: This demonstration presents U-Parking, a distributed Ultra-Wideband (UWB)-assisted autonomous parking system. By integrating Large Language Models (LLMs)-assisted planning with robust …
arXiv:2603.04915v1 Announce Type: new Abstract: Smart contracts on public blockchains now manage large amounts of value, and vulnerabilities in these systems can lead to substantial …
arXiv:2603.04918v1 Announce Type: new Abstract: Proximal constraints are fundamental to the stability of the Large Language Model reinforcement learning. While the canonical clipping mechanism in …