Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Mele…
arXiv:2610.02140v1 Announce Type: new Abstract: Introducing new capabilities to frontier models has long been the goal of posttraining, which predomin…
arXiv:2610.02131v1 Announce Type: new Abstract: We study linear programming (LP) representations and strongly polynomial algorithms for robust Markov…
arXiv:2610.02126v1 Announce Type: new Abstract: We explore catastrophic forgetting in the context of large pre-trained models. By considering forgetti…
arXiv:2610.02098v1 Announce Type: new Abstract: Mechanistic interpretability aims to recover the internal computations responsible for model behavior.…
arXiv:2610.02067v1 Announce Type: new Abstract: While Low-Rank Adaptation (LoRA) enables efficient task specialization, its learned updates can compro…
arXiv:2610.02058v1 Announce Type: new Abstract: Despite the success of Time Series Foundation Models (TSFMs) on broad benchmarks, their ability to int…
arXiv:2610.02043v1 Announce Type: new Abstract: Schr\"odinger bridge (SB) learns stochastic transport between prescribed initial and target distributi…
arXiv:2610.02039v1 Announce Type: new Abstract: Recent years have witnessed the rapid adoption of reinforcement learning (RL) in large language model…
arXiv:2610.02033v1 Announce Type: new Abstract: Individual mobility trajectories support urban analysis and location-based services, yet most trajecto…
arXiv:2610.02015v1 Announce Type: new Abstract: Recent advances in LLM reasoning models---driven primarily by the paradigm of post-training via reinfo…
arXiv:2610.02013v1 Announce Type: new Abstract: Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, bu…
arXiv:2610.02012v1 Announce Type: new Abstract: Reinforcement learning (RL) is a powerful paradigm for training agents, yet its success rests on domai…
arXiv:2610.01981v1 Announce Type: new Abstract: Universal approximation is a necessary qualitative property of learning architectures to benefit from…
arXiv:2610.01980v1 Announce Type: new Abstract: Decision-focused learning for linear optimization is complicated by the discontinuity of the optimizer…
arXiv:2610.01974v1 Announce Type: new Abstract: Simulation and experimental measurements provide complementary data for learning spatiotemporal physic…
arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve…
arXiv:2610.01962v1 Announce Type: new Abstract: The ability of vision-language models (VLMs) to associate visual identities with biographical informat…
arXiv:2610.01955v1 Announce Type: new Abstract: Outcome-based reinforcement learning can train language models to forecast real-world events, but prio…
arXiv:2610.01951v1 Announce Type: new Abstract: Top-two algorithms are simple and effective for fixed-confidence best-arm identification, but their sh…