For An Exciting Tomorrow
arXiv:2512.24492v1 Announce Type: cross Abstract: Congenital heart disease remains the most common congenital anomaly and a leading cause of neonatal…
arXiv:2512.23777v1 Announce Type: cross Abstract: This study investigates fraud detection in ride hailing platforms through Graph Neural Networks (GNNs),focusing on…
arXiv:2511.18869v2 Announce Type: replace-cross Abstract: Evaluating song aesthetics is challenging due to the multidimensional nature of musical perception and the…
arXiv:2512.24478v1 Announce Type: cross Abstract: Causal discovery from observational data remains fundamentally limited by identifiability constraints. Recent work has explored…
arXiv:2512.20629v2 Announce Type: replace-cross Abstract: This study proposes a multi-agent language framework that enables continual strategy evolution without fine-tuning the…
arXiv:2512.22941v1 Announce Type: cross Abstract: Heterogeneity is a fundamental property in multi-agent reinforcement learning (MARL), which is closely related not…
arXiv:2512.22953v1 Announce Type: cross Abstract: Two divergence regimes dominate modern alignment practice. Supervised fine-tuning and many distillation-style objectives implicitly minimize…
arXiv:2512.21798v2 Announce Type: replace-cross Abstract: Synthetic financial data provides a practical solution to the privacy, accessibility, and reproducibility challenges that…
arXiv:2512.22199v1 Announce Type: new Abstract: Retrieval-Augmented Generation RAG systems enhance large language models by grounding responses in external knowledge bases,…