1 code implementation • 7 Jun 2023 • Haiyang Xu, Qinghao Ye, Xuan Wu, Ming Yan, Yuan Miao, Jiabo Ye, Guohai Xu, Anwen Hu, Yaya Shi, Guangwei Xu, Chenliang Li, Qi Qian, Maofei Que, Ji Zhang, Xiao Zeng, Fei Huang
In addition, to facilitate a comprehensive evaluation of video-language models, we carefully build the largest human-annotated Chinese benchmarks covering three popular video-language tasks of cross-modal retrieval, video captioning, and video category classification.
no code implementations • 20 Oct 2021 • Yidan Hu, Yong liu, Chunyan Miao, Gongqi Lin, Yuan Miao
In this paper, we propose a novel explanation generation framework, named Hierarchical Aspect-guided explanation Generation (HAG), for explainable recommendation.
no code implementations • 25 Oct 2020 • Gongqi Lin, Yuan Miao, Xiaoyong Yang, Wenwu Ou, Lizhen Cui, Wei Guo, Chunyan Miao
To investigate machine comprehension models' ability in handling the commonsense knowledge, we created a Question and Answer Dataset with common knowledge of Synonyms (QADS).
no code implementations • 14 Oct 2020 • Yuan Miao, Enej Ilievski, Oleksandr Gamayun
Using the algebro-geometric approach, we study the structure of semi-classical eigenstates in a weakly-anisotropic quantum Heisenberg spin chain.
Statistical Mechanics Strongly Correlated Electrons High Energy Physics - Theory Mathematical Physics Mathematical Physics Quantum Physics
no code implementations • 22 Jul 2020 • Yonghui Xu, Shengjie Sun, Yuan Miao, Dong Yang, Xiaonan Meng, Yi Hu, Ke Wang, Hengjie Song, Chuanyan Miao
Knowledge graph embedding, which aims to learn the low-dimensional representations of entities and relationships, has attracted considerable research efforts recently.
no code implementations • 8 Sep 2019 • Yidan Hu, Gongqi Lin, Yuan Miao, Chunyan Miao
In this research, we propose a system which aims to allow computers to read articles and answer related questions with commonsense knowledge like a human being for CAT level 2.
no code implementations • 5 Sep 2019 • Yuan Miao, Gongqi Lin, Yidan Hu, Chunyan Miao
In order to be able to compare the difference between people reading and machines reading, we proposed a test called (reading) Comprehension Ability Test (CAT). CAT is similar to Turing test, passing of which means we cannot differentiate people from algorithms in term of their comprehension ability.
no code implementations • 25 Jan 2019 • Oleksandr Gamayun, Yuan Miao, Enej Ilievski
We investigate the dynamics of spin in the axially anisotropic Landau--Lifshitz field theory with a magnetic domain wall initial condition.
Statistical Mechanics Mathematical Physics Mathematical Physics Exactly Solvable and Integrable Systems