7 citations · 20 across the 15 of their papers we have counts for
15 papers
GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence
Zhihua Wen, Zhiliang Tian, Wei Wu +4
Conditional story generation is significant in human-machine interaction, particularly in producing stories with complex plots. While Large language models (LLMs) perform well on m…
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz
Tao Sun, Congliang Chen, Peng Qiao +3
Sign-based stochastic methods have gained attention due to their ability to achieve robust performance despite using only the sign information for parameter updates. However, the c…
DaMSTF: Domain Adversarial Learning Enhanced Meta Self-Training for Domain Adaptation
Menglong Lu, Zhen Huang, Yunxiang Zhao +3
Self-training emerges as an important research line on domain adaptation. By taking the model's prediction as the pseudo labels of the unlabeled data, self-training bootstraps the…
Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification
Menglong Lu, Zhen Huang, Zhiliang Tian +3
Text classification is a fundamental task for natural language processing, and adapting text classification models across domains has broad applications. Self-training generates ps…
End-to-End Word-Level Pronunciation Assessment with MASK Pre-training
Yukang Liang, Kaitao Song, Shaoguang Mao +6
Pronunciation assessment is a major challenge in the computer-aided pronunciation training system, especially at the word (phoneme)-level. To obtain word (phoneme)-level scores, cu…
DiffusionNER: Boundary Diffusion for Named Entity Recognition
Yongliang Shen, Kaitao Song, Xu Tan +3
In this paper, we propose DiffusionNER, which formulates the named entity recognition task as a boundary-denoising diffusion process and thus generates named entities from noisy sp…