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arXiv:2602.15362v1 Announce Type: new Abstract: Modern web dashboards and enterprise applications increasingly rely on complex, distributed microservices architectures. While these architectures offer scalability, they introduce...
arXiv:2602.15364v1 Announce Type: new Abstract: AI watermarking embeds invisible signals within images to provide provenance information and identify content as AI-generated. In this paper, we...
arXiv:2602.15367v1 Announce Type: new Abstract: Reinforcement learning (RL) has achieved notable performance in high-dimensional sequential decision-making tasks, yet remains limited by low sample efficiency, sensitivity...
arXiv:2602.15368v1 Announce Type: new Abstract: Generative models have made it possible to synthesize highly realistic images, potentially providing an abundant data source for training machine...
arXiv:2602.15371v1 Announce Type: new Abstract: Over the last 35 years, the sharing of medical data and models for research has evolved from sneakernet to the...
arXiv:2602.15373v1 Announce Type: new Abstract: Language models exhibit systematic performance gaps when processing text in non-standard language varieties, yet their ability to comprehend variety-specific slang...
arXiv:2602.15376v1 Announce Type: new Abstract: Cryptographic digests (e.g., MD5, SHA-256) are designed to provide exact identity. Any single-bit change in the input produces a completely...
arXiv:2602.15377v1 Announce Type: new Abstract: Customer service automation has seen growing demand within digital transformation. Existing approaches either rely on modular system designs with extensive...
arXiv:2602.15378v1 Announce Type: new Abstract: Can large language models converse in languages virtually absent from their training data? We investigate this question through a case...
arXiv:2602.15379v1 Announce Type: new Abstract: The increasing size and complexity of modern deep neural networks (DNNs) pose significant challenges for on-device inference on mobile GPUs,...
arXiv:2602.15380v1 Announce Type: new Abstract: Federated learning (FL) allows remote clients to train a global model collaboratively while protecting client privacy. Despite its privacy-preserving benefits,...
arXiv:2602.15381v1 Announce Type: new Abstract: Automatically extracting engaging and high-quality humorous scenes from cinematic titles is pivotal for creating captivating video previews and snackable content,...
arXiv:2602.15382v1 Announce Type: new Abstract: Multi-Agent Systems (MAS) powered by Large Language Models have unlocked advanced collaborative reasoning, yet they remain shackled by the inefficiency...
arXiv:2602.15383v1 Announce Type: new Abstract: Day-to-night unpaired image translation is important to downstream tasks but remains challenging due to large appearance shifts and the lack...
arXiv:2602.15384v1 Announce Type: new Abstract: Web agents based on large language models have demonstrated promising capability in automating web tasks. However, current web agents struggle...
arXiv:2602.15388v1 Announce Type: new Abstract: While leveraging LLMs to automatically generate SystemVerilog assertions (SVAs) from natural language specifications holds great potential, existing techniques face a...
arXiv:2602.15391v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in production environments face a fundamental safety-utility trade-off either a strict filtering mechanisms prevent harmful...
arXiv:2602.15393v1 Announce Type: new Abstract: Standard Mean-Shift algorithms are notoriously sensitive to the bandwidth hyperparameter, particularly in data-scarce regimes where fixed-scale density estimation leads to...
arXiv:2602.15395v1 Announce Type: new Abstract: We study the builder-driven MEV arbitrage on BNB Smart Chain (BSC). BSC's Proposer--Builder Separation (PBS) adopts a leaner design: only...
arXiv:2602.15396v1 Announce Type: new Abstract: Diffusion models often yield highly curved trajectories and noisy score targets due to an uninformative, memoryless forward process that induces...
arXiv:2602.15397v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior instruction-following and training efficiency. Central...
arXiv:2602.15398v1 Announce Type: new Abstract: Autonomous aerospace systems require architectures that balance deterministic real-time control with advanced perception capabilities. This paper presents an integrated system...
arXiv:2602.15399v1 Announce Type: new Abstract: This work considers using reduced basis techniques in connection to (smoothened) total variation regularization in electrical impedance tomography, but analogous...
arXiv:2602.15400v1 Announce Type: new Abstract: A navigable agent needs to understand both high-level semantic instructions and precise spatial perceptions. Building navigation agents centered on Multimodal...