Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2610.01601v1 Announce Type: new Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. Th…
arXiv:2610.01590v1 Announce Type: new Abstract: Continual learners that keep a task-specific adapter in every block of a pre-trained vision transforme…
arXiv:2610.01579v1 Announce Type: new Abstract: Climate downscaling aims to reconstruct fine scale spatial fields from coarse resolution inputs. Evalu…
arXiv:2610.01566v1 Announce Type: new Abstract: Practical Reinforcement Learning (RL) algorithms learn to solve Markov Decision Processes (MDPs) throu…
arXiv:2610.01554v1 Announce Type: new Abstract: Wanda (Sun et al., 2024) prunes large language models by scoring weights independently within each lin…
arXiv:2610.01548v1 Announce Type: new Abstract: As the use of large language models (LLMs) expands, post-training has become increasingly important fo…
arXiv:2610.01537v1 Announce Type: new Abstract: Federated Learning (FL) enables privacy-preserving fine-tuning of Large Language Models (LLMs), yet th…
arXiv:2610.01530v1 Announce Type: new Abstract: In predictive maintenance, early and late RUL prediction errors carry asymmetric consequences, yet hyp…
arXiv:2610.01527v1 Announce Type: new Abstract: Non-Markovian environments are often modeled as Regular Decision Processes (RDPs), where dynamics depe…
arXiv:2610.01522v1 Announce Type: new Abstract: Many scientific and machine learning systems, from molecular dynamics to diffusion models and beyond,…
arXiv:2610.01519v1 Announce Type: new Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural net…
arXiv:2610.01515v1 Announce Type: new Abstract: Adaptive preconditioners accelerate model training, but heterogeneous client geometries can bias feder…
arXiv:2610.01502v1 Announce Type: new Abstract: Diffusion models are a powerful generative paradigm used across multimedia and scientific applications…
arXiv:2610.01494v1 Announce Type: new Abstract: Sheaf Neural Networks generalize scalar-weighted message passing by replacing scalar edge weights with…
arXiv:2610.01459v1 Announce Type: new Abstract: We study logistic regression on linearly separable data under gradient descent with a large constant s…
arXiv:2610.01456v1 Announce Type: new Abstract: Given a set of $n$ points $X$ in a metric space and an integer $k$, max-min diversification aims to se…
arXiv:2610.01453v1 Announce Type: new Abstract: Deep neural networks are increasingly deployed in long-lived systems, where task requirements may chan…
arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochas…
arXiv:2610.01435v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong predictive performance through in-context learning, ye…
arXiv:2610.01426v1 Announce Type: new Abstract: Prescribing the speed of gradient flow on the risk itself, by the dynamics $\dot w=-u(E(w))\nabla E(w)…