97 citations · 206 across the 32 of their papers we have counts for
41 papers
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation
Chenglong Wang, Hang Zhou, Yimin Hu +5
Applying Reinforcement Learning (RL) to sequence generation models enables the direct optimization of long-term rewards (\textit{e.g.,} BLEU and human feedback), but typically requ…
Learning Evaluation Models from Large Language Models for Sequence Generation
Chenglong Wang, Hang Zhou, Kaiyan Chang +6
Automatic evaluation of sequence generation, traditionally reliant on metrics like BLEU and ROUGE, often fails to capture the semantic accuracy of generated text sequences due to t…
Towards Robust Aspect-based Sentiment Analysis through Non-counterfactual Augmentations
Xinyu Liu, Yan Ding, Kaikai An +4
While state-of-the-art NLP models have demonstrated excellent performance for aspect based sentiment analysis (ABSA), substantial evidence has been presented on their lack of robus…
Recent Advances in Direct Speech-to-text Translation
Chen Xu, Rong Ye, Qianqian Dong +5
Recently, speech-to-text translation has attracted more and more attention and many studies have emerged rapidly. In this paper, we present a comprehensive survey on direct speech…
Understanding Parameter Sharing in Transformers
Ye Lin, Mingxuan Wang, Zhexi Zhang +3
Parameter sharing has proven to be a parameter-efficient approach. Previous work on Transformers has focused on sharing parameters in different layers, which can improve the perfor…
Modality Adaption or Regularization? A Case Study on End-to-End Speech Translation
Yuchen Han, Chen Xu, Tong Xiao +1
Pre-training and fine-tuning is a paradigm for alleviating the data scarcity problem in end-to-end speech translation (E2E ST). The commonplace "modality gap" between speech and te…