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arXiv:2603.03862v1 Announce Type: new Abstract: As mental health issues continue to rise globally, there is an increasing demand for accessible and scalable therapeutic solutions. Many...
arXiv:2603.03865v1 Announce Type: new Abstract: While federated learning protects data privacy, it also makes the model update process vulnerable to long-term stealthy perturbations. Existing studies...
arXiv:2603.03867v1 Announce Type: new Abstract: Link prediction (LP) plays a central role in graph-based applications, particularly in social recommendation. However, real-world graphs often reflect structural...
arXiv:2603.03871v1 Announce Type: new Abstract: Infrared and visible image fusion (IVIF) integrates complementary modalities to enhance scene perception. Current methods predominantly focus on optimizing handcrafted...
arXiv:2603.03872v1 Announce Type: new Abstract: Large Reasoning Models have demonstrated remarkable performance with the advancement of test-time scaling techniques, which enhances prediction accuracy by generating...
arXiv:2603.03875v1 Announce Type: new Abstract: Empirical research in reverse engineering and software protection is crucial for evaluating the efficacy of methods designed to protect software...
arXiv:2603.03878v1 Announce Type: new Abstract: The exponential growth of AI has created unprecedented demand for computational resources, pushing chip designs to the limit while simultaneously...
arXiv:2603.03879v1 Announce Type: new Abstract: Estimating the 6D pose of objects from a single RGB image is a critical task for robotics and extended reality...
arXiv:2603.03880v1 Announce Type: new Abstract: Software-hardware co-design is essential for optimizing in-memory computing (IMC) hardware accelerators for neural networks. However, most existing optimization frameworks target...
arXiv:2603.03881v1 Announce Type: new Abstract: As LLM-driven agents begin to autonomously navigate the web, their ability to interpret and respond to manipulative interface design becomes...
arXiv:2603.03882v1 Announce Type: new Abstract: Lip synchronization aims to generate realistic talking videos that match given audio, which is essential for high-quality video dubbing. However,...
arXiv:2603.03884v1 Announce Type: new Abstract: Topic localization aims to identify spans of text that express a given topic defined by a name and description. To...
arXiv:2603.03892v1 Announce Type: new Abstract: In this paper, we present a network structure for classifying metadata of cuneiform tablets. The problem is of practical importance,...
arXiv:2603.03897v1 Announce Type: new Abstract: Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods for robot skill adaptation from...
arXiv:2603.03899v1 Announce Type: new Abstract: For an offline-first collaborative application to operate in true peer-to-peer fashion, its collaborative features must function even in environments where...
arXiv:2603.03902v1 Announce Type: new Abstract: Time series forecasting, which predicts future values from past observations, plays a central role in many domains and has driven...
arXiv:2603.03903v1 Announce Type: new Abstract: Building reliable classifiers is a fundamental challenge for deploying machine learning in real-world applications. A reliable system should not only...
arXiv:2603.03906v1 Announce Type: new Abstract: Synthetic data is increasingly used to support research without exposing sensitive user content. Social media data is one of the...
arXiv:2603.03907v1 Announce Type: new Abstract: Image aesthetic assessment (IAA) has extensive applications in content creation, album management, and recommendation systems, etc. In such applications, it...
arXiv:2603.03909v1 Announce Type: new Abstract: Pangenomics uses graph-based models to represent and study the genetic variation between individuals of the same species or between different...
arXiv:2603.03911v1 Announce Type: new Abstract: Web security demands rapid response capabilities to evolving cyber threats. Agentic Artificial Intelligence (AI) promises automation, but the need for...
arXiv:2603.03915v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated significant potential in developing Role-Playing Agents (RPAs). However, current research primarily evaluates RPAs using...
arXiv:2603.03919v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances the capabilities of large language models (LLMs) by incorporating external knowledge, but its reliance on potentially...
arXiv:2603.03920v1 Announce Type: new Abstract: Model Merging (MM) has emerged as a scalable paradigm for multi-task learning (MTL), enabling multiple task-specific models to be integrated...