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arXiv:2505.11708v2 Announce Type: replace Abstract: Reinforcement Learning (RL) agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain opaque, hindering trust, debugging,...
arXiv:2505.11998v4 Announce Type: replace Abstract: Catastrophic forgetting has remained a critical challenge for deep neural networks in Continual Learning (CL) as it undermines consolidated knowledge...
arXiv:2505.12025v2 Announce Type: replace Abstract: In many real-world applications, users rely on natural language instructions to guide large language models (LLMs) across a wide range...
arXiv:2505.12513v3 Announce Type: replace Abstract: Global tree species mapping using remote sensing data is vital for biodiversity monitoring, forest management, and ecological research. However, progress...
arXiv:2505.12540v4 Announce Type: replace Abstract: We introduce the first method for translating text embeddings from one vector space to another without any paired data, encoders,...
arXiv:2505.12560v4 Announce Type: replace Abstract: Existing datasets available for crosslinguistic investigations have tended to focus on large amounts of data for a small group of...
arXiv:2505.12592v2 Announce Type: replace Abstract: Prompts are the interface for eliciting the capabilities of large language models (LLMs). Understanding their structure and components is critical...
arXiv:2505.14125v3 Announce Type: replace Abstract: Biological brains learn continually from a stream of unlabeled data, while integrating specialized information from sparsely labeled examples without compromising...
arXiv:2505.14313v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly evaluated on reasoning tasks, yet their logical abilities remain contested. To address this, we...
arXiv:2505.14932v3 Announce Type: replace Abstract: Reasoning in language models is difficult to evaluate: natural-language traces are unverifiable, symbolic datasets are too small, and most benchmarks...
arXiv:2505.15139v2 Announce Type: replace Abstract: Gaining insights into the structural and functional mechanisms of the brain has been a longstanding focus in neuroscience research, particularly...
arXiv:2505.15556v2 Announce Type: replace Abstract: The increasing prevalence of mental disorders globally highlights the urgent need for effective digital screening methods that can be used...
arXiv:2505.16305v2 Announce Type: replace Abstract: Tensor CANDECOMP/PARAFAC decomposition (CPD) is a fundamental model for tensor reconstruction. Although the Bayesian framework allows for principled uncertainty quantification...
arXiv:2505.16358v2 Announce Type: replace Abstract: We introduce a game-theoretic framework examining strategic interactions between a platform and its content creators in the presence of AI-generated...
arXiv:2505.17902v3 Announce Type: replace Abstract: In an era defined by rapid data evolution, traditional Machine Learning (ML) models often struggle to adapt to dynamic environments....
arXiv:2505.18289v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are key tools for graph representation learning, demonstrating strong results across diverse prediction tasks. In this...
arXiv:2505.18663v3 Announce Type: replace Abstract: Diffusion Transformers (DiTs) have emerged as the state-of-the-art architecture for video generation, yet their computational and memory demands hinder practical...
arXiv:2505.18832v3 Announce Type: replace Abstract: Understanding how knowledge is distributed across the layers of generative models is crucial for improving interpretability, controllability, and adaptation. While...
arXiv:2505.19328v4 Announce Type: replace Abstract: Ambivalence and hesitancy (A/H), a closely related construct, is the primary reasons why individuals delay, avoid, or abandon health behaviour...
arXiv:2505.19442v4 Announce Type: replace Abstract: Controllable code generation, the ability to synthesize code that follows a specified style while maintaining functionality, remains a challenging task....
arXiv:2505.19459v2 Announce Type: replace Abstract: Joint Energy-based Models (JEMs) are well known for their ability to unify classification and generation within a single framework. Despite...
arXiv:2505.19514v4 Announce Type: replace Abstract: Prompt quality plays a critical role in the performance of large language models (LLMs), motivating a growing body of work...
arXiv:2505.20298v3 Announce Type: replace Abstract: Manga, or Japanese comics, is a richly multimodal narrative form that blends images and text in complex ways. Teaching large...
arXiv:2505.20347v2 Announce Type: replace Abstract: Recent advances have demonstrated the effectiveness of Reinforcement Learning (RL) in improving the reasoning capabilities of Large Language Models (LLMs)....