Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2609.18964v2 Announce Type: replace Abstract: Federated Reinforcement Learning (FRL) enables collaborative policy learning across distributed ag…
arXiv:2608.26423v2 Announce Type: replace Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for develo…
arXiv:2608.05446v2 Announce Type: replace Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track p…
arXiv:2607.25531v2 Announce Type: replace Abstract: Contemporary machine learning struggles to learn continually, reuse prior knowledge, and expose a…
arXiv:2607.23634v2 Announce Type: replace Abstract: Attention enables context modeling via query-key scoring with softmax normalization. Driven by ind…
arXiv:2607.17508v3 Announce Type: replace Abstract: We introduce Retrieval-Augmented Interpretable Learning (RAIL), a probabilistic meta-learning fram…
arXiv:2607.10729v4 Announce Type: replace Abstract: Molecular property models are commonly evaluated by holding out Bemis-Murcko scaffolds, yet a scaf…
arXiv:2607.09042v2 Announce Type: replace Abstract: Reinforcement learning is increasingly used to fine-tune vision-language-action (VLA) models, but…
arXiv:2607.04332v2 Announce Type: replace Abstract: In this paper, we consider the setting where large language models (LLMs) are trained using reinfo…
arXiv:2606.26497v2 Announce Type: replace Abstract: Bayesian filtering of partially and noisily observed dynamical systems seeks to infer the evolving…
arXiv:2606.23044v3 Announce Type: replace Abstract: Numbers have algebraic structure that standard neural embeddings often fail to expose. We introduc…
arXiv:2606.22994v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) have become an important tool for unsupervised concept discovery in lar…
arXiv:2606.19317v3 Announce Type: replace Abstract: A longstanding goal of research on interpretable deep learning is to replace opaque neural computa…
arXiv:2606.16786v2 Announce Type: replace Abstract: Algorithmic explanations are intended to help stakeholders understand opaque algorithmic decisions…
arXiv:2606.10944v2 Announce Type: replace Abstract: We introduce a new tool, Express, for converting a non-causal attention approximation into a causa…
arXiv:2606.04931v2 Announce Type: replace Abstract: Mean-based algorithms are online learning algorithms that assign low probability to actions with l…
arXiv:2606.03927v2 Announce Type: replace Abstract: The Forward-Forward (FF) algorithm offers a computationally efficient and biologically plausible a…
arXiv:2606.00880v2 Announce Type: replace Abstract: Continual reinforcement learning (RL) aims to produce agents that never stop adapting to new tasks…
arXiv:2605.31289v3 Announce Type: replace Abstract: Representation learning is a powerful tool for spatio-temporal abstraction within reinforcement le…
arXiv:2605.23753v2 Announce Type: replace Abstract: Knowledge graphs (KGs) offer a rich representation for relational knowledge, but their irregular s…