Latest AI/ML News
9894 articles · arXiv cs.LG
arXiv:2610.00707v1 Announce Type: new Abstract: Large Language Models (LLMs) have been used for novel discovery of algorithms, theorems, drugs, and ot…
arXiv:2610.00704v1 Announce Type: new Abstract: Natural-language skills are textual procedural memories through which large language model (LLM) agent…
arXiv:2610.00683v1 Announce Type: new Abstract: We introduce Grand Canonical Generators (GCG), a generative framework that extends Boltzmann generator…
arXiv:2610.00680v1 Announce Type: new Abstract: Curvature is often treated as an intrinsic property of a representation, although its empirical effect…
arXiv:2610.00676v1 Announce Type: new Abstract: Unsupervised skill discovery has emerged as a promising approach for leveraging reward-free datasets t…
arXiv:2610.00675v1 Announce Type: new Abstract: Evolutionary approaches to LLM-driven discovery often generate new programs from a small set of select…
arXiv:2610.00672v1 Announce Type: new Abstract: Protein foundation models support mutation-effect and structural prediction, but predictive performanc…
arXiv:2610.00665v1 Announce Type: new Abstract: Background: Protein language models (PLMs) are increasingly used for sequence generation and property…
arXiv:2610.00661v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, al…
arXiv:2610.00647v1 Announce Type: new Abstract: The representations that language models learn for concepts such as months, weekdays, and places displ…
arXiv:2610.00637v1 Announce Type: new Abstract: We establish non-asymptotic sample complexity bounds for the least-squares estimation of vector autore…
arXiv:2610.00620v1 Announce Type: new Abstract: Grokking refers to the delayed emergence of validation-set generalization after a model has already ov…
arXiv:2610.00615v1 Announce Type: new Abstract: One might think that learning the identity function with a deep linear residual network is trivial - t…
arXiv:2610.00604v1 Announce Type: new Abstract: Vision-language-action policies often see only one or a few recent frames, which makes it difficult to…
arXiv:2610.00592v1 Announce Type: new Abstract: In partially observable reinforcement learning (RL), a later observation can make stored information o…
arXiv:2610.00586v1 Announce Type: new Abstract: Activation memory, not compute, limits CNN inference on constrained hardware such as microcontrollers.…
arXiv:2610.00580v1 Announce Type: new Abstract: In collaborative foundation model fine-tuning, client data is rarely homogeneous. Instead, clients typ…
arXiv:2610.00574v1 Announce Type: new Abstract: Multi-reward reinforcement learning trains large language models to satisfy multiple behavioral object…
arXiv:2610.00564v1 Announce Type: new Abstract: Operator learning on probability measures can be accomplished with transformers. For measures with pol…
arXiv:2610.00563v1 Announce Type: new Abstract: This paper presents a preliminary study of an alternative to the affine transformation underlying conv…