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cs.CL2024

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Tian Liang, Zhiwei He, Wenxiang Jiao +6

Modern large language models (LLMs) like ChatGPT have shown remarkable performance on general language tasks but still struggle on complex reasoning tasks, which drives the researc…

cs.CL2024

Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models

Zhiwei He, Binglin Zhou, Hongkun Hao +5

Text watermarking technology aims to tag and identify content produced by large language models (LLMs) to prevent misuse. In this study, we introduce the concept of cross-lingual c…

cs.CL2024

Cross-modality Data Augmentation for End-to-End Sign Language Translation

Jinhui Ye, Wenxiang Jiao, Xing Wang +2

End-to-end sign language translation (SLT) aims to convert sign language videos into spoken language texts directly without intermediate representations. It has been a challenging…

cs.CL2024

Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model

Zhiwei He, Xing Wang, Wenxiang Jiao +4

Insufficient modeling of human preferences within the reward model is a major obstacle for leveraging human feedback to improve translation quality. Fortunately, quality estimation…

cs.CL2024

Unsupervised Sign Language Translation and Generation

Zhengsheng Guo, Zhiwei He, Wenxiang Jiao +6

Motivated by the success of unsupervised neural machine translation (UNMT), we introduce an unsupervised sign language translation and generation network (USLNet), which learns fro…