Developing Large Language Models (LLMs) with robust long-context capabilities has been the recent research focus, resulting in the emergence of long-context LLMs proficient in …
Z Xu, Z Yang, Y Cui, S Wang - arXiv preprint arXiv:2306.15273, 2023 - arxiv.org
In the field of machine reading comprehension (MRC), existing systems have surpassed the average performance of human beings in many tasks like SQuAD. However, there is still a …
The rapid development and application of natural language generation (NLG) techniques has revolutionized the field of automatic text production. However, these techniques are still …
H Sun, W Xu, W Liu, J Luan, B Wang… - Proceedings of the …, 2024 - aclanthology.org
Recent advances in large language models (LLMs) have revolutionized the landscape of reasoning tasks. To enhance the capabilities of LLMs to emulate human reasoning, prior …
S Wang, Z Wei, J Xu, T Li, Z Fan - arXiv preprint arXiv:2301.08913, 2023 - arxiv.org
Recent pre-trained language models (PLMs) equipped with foundation reasoning skills have shown remarkable performance on downstream complex tasks. However, the …
Logical reasoning on natural language is one of the most challenging tasks for deep learning models. There has been an increasing interest in developing new benchmarks to …
M Wu, T Sun, Z Wang, J Duan - Applied Sciences, 2023 - mdpi.com
In recent years, with the advancement of natural language processing techniques and the release of models like ChatGPT, how language models understand questions has become a …
W Zhong, T Ma, J Wang, J Yin, T Zhao, CY Lin… - arXiv preprint arXiv …, 2022 - arxiv.org
This paper presents ReasonFormer, a unified reasoning framework for mirroring the modular and compositional reasoning process of humans in complex decision-making …
S Wang, Z Wei, J Xu, T Li, Z Fan - IEEE/ACM Transactions on …, 2023 - ieeexplore.ieee.org
Recent pre-trained language models (PLMs) equipped with foundation reasoning skills have shown remarkable performance on downstream complex tasks. However, the …