Quality follows upgrading
Ever a pioneer, ever a student — learning through our mistakes and failures
전체 전문분석자료
arXiv:2603.03777v1 Announce Type: new Abstract: A typical Vertical Federated Learning (VFL) scenario involves several participants collaboratively training a machine learning model, where each party has …
arXiv:2603.03778v1 Announce Type: new Abstract: We study the Inverse Contextual Bandit (ICB) problem, in which a learner seeks to optimize a policy while an observer, …
arXiv:2603.03796v1 Announce Type: new Abstract: When continual test-time adaptation (TTA) persists over the long term, errors accumulate in the model and further cause it to …
arXiv:2603.03805v1 Announce Type: new Abstract: Relational Databases (RDBs) are the backbone of modern business, yet they lack foundation models comparable to those in text or …
arXiv:2603.03818v1 Announce Type: new Abstract: Continual learning is a long-standing challenge in robot policy learning, where a policy must acquire new skills over time without …
arXiv:2603.03820v1 Announce Type: new Abstract: Interactive recommender systems (IRS) are increasingly optimized with Reinforcement Learning (RL) to capture the sequential nature of user-system dynamics. However, …
arXiv:2603.03830v1 Announce Type: new Abstract: Overparameterized machine learning (ML) methods such as neural networks may be prohibitively resource intensive for devices with limited computational capabilities. …
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:2603.03872v1 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:2603.02676v1 Announce Type: new Abstract: Large language models suffer from content effects in reasoning tasks, particularly in multi-lingual contexts. We introduce a novel method that …
arXiv:2603.02684v1 Announce Type: new Abstract: Subtle and indirect hate speech remains an underexplored challenge in online safety research, particularly when harmful intent is embedded within …