Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2603.11546v2 Announce Type: replace Abstract: Many real-world machine learning tasks are anti-causal: they require inferring latent causes from…
arXiv:2603.02221v3 Announce Type: replace Abstract: In clinical tabular prediction, classical machine learning models with feature engineering often o…
arXiv:2602.18639v2 Announce Type: replace Abstract: World models learned from high-dimensional visual observations allow agents to make decisions and…
arXiv:2602.18182v5 Announce Type: replace Abstract: AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired fro…
arXiv:2602.18181v2 Announce Type: replace Abstract: This work presents SeedFlood, a new approach to decentralized LLM fine-tuning designed to scale ac…
arXiv:2601.23135v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a key driver of language model reasoning. Among RL algorith…
arXiv:2601.06701v2 Announce Type: replace Abstract: Complex AI systems make better predictions but often lack transparency, limiting trustworthiness,…
arXiv:2512.05990v2 Announce Type: replace Abstract: Memory consolidation determines both what a learner can do now and which changes remain implementa…
arXiv:2510.24046v2 Announce Type: replace Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions bet…
arXiv:2510.23191v2 Announce Type: replace Abstract: Predictive benchmarking, evaluating machine learning models based on predictive performance and co…
arXiv:2510.08944v2 Announce Type: replace Abstract: Real-world time-series regression often involves non-stationarity, heteroscedasticity, and regime…
arXiv:2509.20789v5 Announce Type: replace Abstract: The remarkable success of modern AI has been closely tied to scaling laws, yet the finite supply o…
arXiv:2509.11337v2 Announce Type: replace Abstract: Adversarial training has been widely studied in recent years due to its role in improving model ro…
arXiv:2508.16748v2 Announce Type: replace Abstract: Prevalent multimodal self-supervised learning (SSL) methods rely on the redundancy assumption: tha…
arXiv:2508.13408v3 Announce Type: replace Abstract: Chemical Language Models (CLMs) are increasingly used in de novo drug design, driven by recent gro…
arXiv:2506.11030v2 Announce Type: replace Abstract: Training neural networks has traditionally relied on backpropagation (BP), a gradient-based algori…
arXiv:2505.16741v5 Announce Type: replace Abstract: Minimum attention applies the least action principle in changes of control concerning state and ti…
arXiv:2505.03155v2 Announce Type: replace Abstract: Policy gradient (PG) methods have played an essential role in the empirical successes of reinforce…
arXiv:2503.16311v2 Announce Type: replace Abstract: Masked modeling has emerged as a robust self-supervised learning framework. However, most methods…
arXiv:2502.04892v2 Announce Type: replace Abstract: Learning robust representations from functional magnetic resonance imaging (fMRI) is fundamentally…