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arXiv:2506.09630v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used for synthetic tabular data generation through in-context learning (ICL), offering a practical solution...
arXiv:2506.10912v3 Announce Type: replace Abstract: Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task...
arXiv:2506.11136v3 Announce Type: replace Abstract: Foundation Vision Encoders have become essential for a wide range of dense vision tasks. However, their low-resolution spatial feature outputs...
arXiv:2506.11300v2 Announce Type: replace Abstract: Curriculum learning-organizing training data from easy to hard-has improved efficiency across machine learning domains, yet remains underexplored for language model...
arXiv:2506.11558v4 Announce Type: replace Abstract: Large Language Models (LLMs) have recently been extended to the video domain, enabling sophisticated video-language understanding. However, existing Video LLMs...
arXiv:2506.11743v2 Announce Type: replace Abstract: Graph coarsening aims to diminish the size of a graph to lighten its memory footprint, and has numerous applications in...
arXiv:2506.14790v2 Announce Type: replace Abstract: Recurring concept drift poses a dual challenge in online time series forecasting: mitigating catastrophic forgetting while adhering to strict privacy...
arXiv:2506.16206v4 Announce Type: replace Abstract: Many-valued models generalise the structures from classical model theory by defining truth values for a model with an arbitrary algebra....
arXiv:2506.17697v2 Announce Type: replace Abstract: The recent development of Large Language Models (LLMs) enables the rise of App agents that interpret user intent and operate...
arXiv:2506.22899v2 Announce Type: replace Abstract: Neural Cellular Automata (NCAs) are bio-inspired dynamical systems in which identical cells iteratively apply a learned local update rule to...
arXiv:2506.23734v2 Announce Type: replace Abstract: Black-box coevolution in mixed-motive games is often undermined by opponent-drift non-stationarity and noisy rollouts, which distort progress signals and can...
arXiv:2507.01063v2 Announce Type: replace Abstract: Online dating platforms have fundamentally transformed the formation of romantic relationships, with millions of users worldwide relying on algorithmic matching...
arXiv:2507.01782v3 Announce Type: replace Abstract: Symbiotic Backscatter Communication (SBC) has emerged as a spectrum-efficient and low-power communication technology, where backscatter devices (BDs) modulate and reflect...
arXiv:2507.06602v3 Announce Type: replace Abstract: Modern RAN operate in highly dynamic and heterogeneous environments, where hand-tuned, rule-based RRM algorithms often underperform. While RL can surpass...
arXiv:2507.09071v2 Announce Type: replace Abstract: Large vision-language models (VLMs) enable joint processing of text and images. However, incorporating vision data significantly increases the prompt length,...
arXiv:2507.09204v2 Announce Type: replace Abstract: Research on environmental risk modeling relies on numerous indicators to quantify the magnitude and frequency of extreme climate events, their...
arXiv:2507.09651v2 Announce Type: replace Abstract: Gas transport across cell membrane is a very important process in biochemistry which is essential for many crucial tasks, including...
arXiv:2507.13332v3 Announce Type: replace Abstract: Length generalization, the ability to solve problems of longer sequences than those observed during training, poses a core challenge of...
arXiv:2507.18988v2 Announce Type: replace Abstract: The rapid advancement of image-generation technologies has made it possible for anyone to create photorealistic images using generative models, raising...
arXiv:2507.20072v2 Announce Type: replace Abstract: Equation discovery is a fundamental learning task for uncovering the underlying dynamics of complex systems, with wide-ranging applications in areas...
arXiv:2507.22134v4 Announce Type: replace Abstract: Generative AI shifts interaction toward intent-based outcome specification, despite user intents being inherently vague, fluid, and evolving. While a growing...
arXiv:2507.23599v3 Announce Type: replace Abstract: Efficient and high-accuracy 3D occupancy prediction is crucial for ensuring the performance of autonomous driving (AD) systems. However, many existing...
arXiv:2508.00282v3 Announce Type: replace Abstract: Humans constantly generate a diverse range of tasks guided by internal motivations. While generative agents powered by large language models...
arXiv:2508.02197v2 Announce Type: replace Abstract: We present a message passing approach to Expected Free Energy (EFE) minimization on factor graphs, based on the theory introduced...