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pro vyhledávání: '"Lee, Seungpil"'
Autor:
Lee, Hosung, Kim, Sejin, Lee, Seungpil, Hwang, Sanha, Lee, Jihwan, Lee, Byung-Jun, Kim, Sundong
This paper introduces ARCLE, an environment designed to facilitate reinforcement learning research on the Abstraction and Reasoning Corpus (ARC). Addressing this inductive reasoning benchmark with reinforcement learning presents these challenges: a v
Externí odkaz:
http://arxiv.org/abs/2407.20806
Autor:
Lee, Seungpil, Sim, Woochang, Shin, Donghyeon, Seo, Wongyu, Park, Jiwon, Lee, Seokki, Hwang, Sanha, Kim, Sejin, Kim, Sundong
The existing methods for evaluating the inference abilities of Large Language Models (LLMs) have been results-centric, making it difficult to assess the inference process. We introduce a new approach using the Abstraction and Reasoning Corpus (ARC) d
Externí odkaz:
http://arxiv.org/abs/2403.11793
Publikováno v:
In Applied Energy 15 November 2019 254
Publikováno v:
In Applied Thermal Engineering September 2018 142:68-78
Autor:
Lee, Seungpil, Park, Sungwook
Publikováno v:
In Energy 15 February 2017 121:433-448
Akademický článek
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Autor:
Li, Yan, Lee, Seungpil, Oowada, Ken, Nguyen, Hao, Nguyen, Qui, Mokhlesi, Nima, Hsu, Cynthia, Li, Jason, Ramachandra, Venky, Kamei, Teruhiko, Higashitani, Masaaki, Pham, Tuan, Honma, Mitsuaki, Watanabe, Yoshihisa, Ino, Kazumi, Le, Binh, Woo, Byungki, Htoo, Khin, Tseng, Tai-Yuan, Pham, Long
Publikováno v:
2012 IEEE International Solid-State Circuits Conference; 1/ 1/2012, p436-437, 2p