Results 131 to 140 of about 150,050 (298)
Advanced Science, EarlyView.This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao +9 more
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Wittgenstein and Heidegger: Language as universal medium and inexpressibility of semantics
, 2012 Miloš Šumonja
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, 1996 34 pages. Appeared in in Proceedings of the 1996 CLiCS Summer School, Isaac Newton Institute, P. Dybjer and A. Pitts, eds.
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Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors
Advanced Science, EarlyView.Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu +4 more
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Advanced Science, EarlyView.Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung +39 more
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Advanced Science, EarlyView.A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen +15 more
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Model-free incremental learning of the semantics of manipulation actions [PDF]
, 2014 Eren Erdal Aksoy +2 more
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Robust Semantics for Semantic Parsing.
, 2014 The paper presents a robust semantics for NLP applications including QA, text entailment and SMT that combines a (fairly) standard treatment of logical operators such as negation and quantification (Steedman 2012) with a highly nonstandard paraphrase- and entailment--based semantics of relational terms derived from text data by machine reading (Lewis ...
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