773 citations · 1.1k across the 47 of their papers we have counts for
7 papers · 1 filter
ERNIE-SAT: Speech and Text Joint Pretraining for Cross-Lingual Multi-Speaker Text-to-Speech
Xiaoran Fan, Chao Pang, Tian Yuan +9
Speech representation learning has improved both speech understanding and speech synthesis tasks for single language. However, its ability in cross-lingual scenarios has not been e…
ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages
Yekun Chai, Shuohuan Wang, Chao Pang +3
Software engineers working with the same programming language (PL) may speak different natural languages (NLs) and vice versa, erecting huge barriers to communication and working e…
X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection
Yaqian Han, Yekun Chai, Shuohuan Wang +5
Detecting sarcasm and verbal irony from people's subjective statements is crucial to understanding their intended meanings and real sentiments and positions in social scenarios. Th…
X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications
Junyuan Shang, Shuohuan Wang, Yu Sun +4
This paper describes our winning system on SemEval 2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts. A replaced token…
ERNIE-UniX2: A Unified Cross-lingual Cross-modal Framework for Understanding and Generation
Bin Shan, Yaqian Han, Weichong Yin +5
Recent cross-lingual cross-modal works attempt to extend Vision-Language Pre-training (VLP) models to non-English inputs and achieve impressive performance. However, these models f…
Clip-Tuning: Towards Derivative-free Prompt Learning with a Mixture of Rewards
Yekun Chai, Shuohuan Wang, Yu Sun +3
Derivative-free prompt learning has emerged as a lightweight alternative to prompt tuning, which only requires model inference to optimize the prompts. However, existing work did n…