Results 271 to 280 of about 3,424,284 (379)

Reward Design Using Large Language Models for Natural Language Explanation of Reinforcement Learning Agent Actions

open access: yesIEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Reinforcement learning (RL) has found applications across diverse domains; however, it grapples with challenges when formulating reward functions and exhibits low exploration efficiency. Recent studies leveraging large language models (LLMs) have made strides in addressing these issues.
Shinya Masadome, Taku Harada
wiley   +1 more source

The Impact of Gaze‐Contingent Textual Enhancement on L2 Collocation Learning from Computer‐Mediated Reading Tasks

open access: yesTESOL Quarterly, EarlyView.
Abstract This study examined if gaze‐contingent textual enhancement could be used as an interactive focus‐on‐form device to promote learning of second language (L2) collocations from computer‐mediated reading tasks. Seventy‐five Chinese ESL users read three English texts that contained twelve target collocations, presented under one of three conditions:
Jookyoung Jung   +5 more
wiley   +1 more source

Surgical gestures—An emerging field for surgical assessment and training

open access: yesUroPrecision, EarlyView.
Abstract As surgical training shifts from a traditional method to a more standardized approach, objective analysis and assessment of surgeon performance has become a key focus. Surgical gestures, defined as the smallest independent units of instrument‐tissue interaction, offer a quantifiable way to analyze surgical performance.
Runzhuo Ma
wiley   +1 more source

On the equivalence of the static and disjunctive well-founded semantics and its computation

open access: bronze, 2001
Stefan Brass   +3 more
openalex   +1 more source

Unveiling large multimodal models in pulmonary CT: A comparative assessment of generative AI performance in lung cancer diagnostics

open access: yesVIEW, EarlyView.
1. The emergence of generative artificial intelligence (Gen‐AI) requires rigorous validation to assess its diagnostic reliability and limitations. 2. Three Gen‐AI models (GPT‐4‐turbo, Gemini‐pro‐vision, and Claude‐3‐opus) performed inconsistently across different diagnostic environments, demonstrating significant internal variability and overall ...
Lihaoyun Huang   +17 more
wiley   +1 more source

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