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전체 전문분석자료
arXiv:2604.05738v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) have achieved expert-level proficiency in interpreting diagnostic imaging. However, current models are predominantly trained on professional …
arXiv:2604.05096v1 Announce Type: new Abstract: Large language models (LLMs) acquire most of their knowledge during pretraining, which ties them to a fixed snapshot of the …
arXiv:2604.04987v1 Announce Type: new Abstract: Speculative sampling (SpS) has been successful in accelerating the decoding throughput of auto-regressive large language models by leveraging smaller draft …
arXiv:2604.05476v1 Announce Type: new Abstract: This work investigates the adaptation of the AlphaZero reinforcement learning algorithm to Tablut, an asymmetric historical board game featuring unequal …
arXiv:2604.05834v1 Announce Type: new Abstract: Multimodal contrastive learning is increasingly enriched by going beyond image-text pairs. Among recent contrastive methods, Symile is a strong approach …
arXiv:2604.05217v1 Announce Type: new Abstract: Neural language models process sequences of words, but the mathematical operations inside them are insensitive to the order in which …
arXiv:2604.05497v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) are emerging as promising alternatives to autoregressive (AR) LLMs. Recently, this paradigm has been extended …
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:2604.05057v1 Announce Type: new Abstract: Blind-spot mass is a Good-Turing framework for quantifying deployment coverage risk in machine learning. In modern ML systems, operational state …
arXiv:2604.05857v1 Announce Type: new Abstract: Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-dependent …
arXiv:2604.05187v1 Announce Type: new Abstract: We propose an extended Fourier neural operator (FNO) architecture for learning state and linear quadratic additive optimal control of systems …
arXiv:2604.05397v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied in high-stakes domains such as finance, healthcare, and education, where reliable multi-turn interactions …