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Tag: math.IT
arXiv:2604.06228v1 Announce Type: new Abstract: We introduce probabilistic language tries (PLTs), a unified representation that makes explicit the prefix structure implicitly defined by any generative …
arXiv:2604.06192v1 Announce Type: new Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains …
arXiv:2604.06613v1 Announce Type: new Abstract: Modern reasoning models continue generating long after the answer is already determined. Across five model configurations, two families, and three …
arXiv:2604.05842v1 Announce Type: new Abstract: Mixture of linear regression is well studied in statistics and machine learning, where the data points are generated probabilistically using …
arXiv:2604.05324v1 Announce Type: new Abstract: Statistical evaluation aims to estimate the generalization performance of a model using held-out i.i.d.\ test data sampled from the ground-truth …
arXiv:2604.03634v1 Announce Type: new Abstract: We prove that temporal averaging over multiple observations can be replaced by algebraic group action on a single observation for …
arXiv:2604.02343v1 Announce Type: cross Abstract: We study the compression of LLM-generated text across lossless and lossy regimes, characterizing a compression-compute frontier where more compression is …
arXiv:2603.23926v1 Announce Type: new Abstract: Online reinforcement learning in infinite-horizon Markov decision processes (MDPs) remains less theoretically and algorithmically developed than its episodic counterpart, with …
arXiv:2603.22465v1 Announce Type: new Abstract: Federated Learning (FL) is constrained by the communication and energy limitations of decentralized edge devices. While gradient sparsification via Top-K …
arXiv:2603.20587v1 Announce Type: new Abstract: When training a neural network for classification, the feature vectors of the training set are known to collapse to the …
arXiv:2603.19322v1 Announce Type: new Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for problems involving discrete …
arXiv:2603.19349v1 Announce Type: new Abstract: Generative AI has transformed the economics of information production, making explanations, proofs, examples, and analyses available at very low cost. …