no code implementations • Findings (EMNLP) 2021 • Deyu Zhou, Yanzheng Xiang, Linhai Zhang, Chenchen Ye, Qian-Wen Zhang, Yunbo Cao
However, most of existing approaches only detect one single path to obtain the answer without considering other correct paths, which might affect the final performance.
no code implementations • COLING 2022 • Xu Zhang, Zejie Liu, Yanzheng Xiang, Deyu Zhou
However such way might not fully explore the knowledge in PTMs as it is constrained by the difficulty of the task.
1 code implementation • 23 Feb 2024 • Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
This approach utilizes contrastive learning to align representations of in-context examples across different positions and introduces a consistency loss to ensure similar representations for inputs with different permutations.
no code implementations • 1 Nov 2023 • Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
Understanding in-context learning (ICL) capability that enables large language models (LLMs) to excel in proficiency through demonstration examples is of utmost importance.