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pro vyhledávání: '"Zheng, Zi'ou"'
When performing complex multi-step reasoning tasks, the ability of Large Language Models (LLMs) to derive structured intermediate proof steps is important for ensuring that the models truly perform the desired reasoning and for improving models' expl
Externí odkaz:
http://arxiv.org/abs/2410.08436
Autor:
Zheng, Zi'ou, Zhu, Xiaodan
Reasoning has been a central topic in artificial intelligence from the beginning. The recent progress made on distributed representation and neural networks continues to improve the state-of-the-art performance of natural language inference. However,
Externí odkaz:
http://arxiv.org/abs/2307.02849
Autor:
Tan, Chao-Hong, Yang, Xiaoyu, Zheng, Zi'ou, Li, Tianda, Feng, Yufei, Gu, Jia-Chen, Liu, Quan, Liu, Dan, Ling, Zhen-Hua, Zhu, Xiaodan
Task-oriented conversational modeling with unstructured knowledge access, as track 1 of the 9th Dialogue System Technology Challenges (DSTC 9), requests to build a system to generate response given dialogue history and knowledge access. This challeng
Externí odkaz:
http://arxiv.org/abs/2012.11937
Publikováno v:
COLING 2020
We explore end-to-end trained differentiable models that integrate natural logic with neural networks, aiming to keep the backbone of natural language reasoning based on the natural logic formalism while introducing subsymbolic vector representations
Externí odkaz:
http://arxiv.org/abs/2011.04044
Publikováno v:
2015 Visual Communications & Image Processing (VCIP); 2015, p1-4, 4p