773 citations · 988 across the 12 of their papers we have counts for
11 papers · 1 filter
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…
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…
ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
Yu Sun, Shuohuan Wang, Shikun Feng +19
Pre-trained models have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. Recent works such as T5 and GPT-3 have shown that scaling up pre-train…
ERNIE-Doc: A Retrospective Long-Document Modeling Transformer
Siyu Ding, Junyuan Shang, Shuohuan Wang +4
Transformers are not suited for processing long documents, due to their quadratically increasing memory and time consumption. Simply truncating a long document or applying the spar…
ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora
Xuan Ouyang, Shuohuan Wang, Chao Pang +4
Recent studies have demonstrated that pre-trained cross-lingual models achieve impressive performance in downstream cross-lingual tasks. This improvement benefits from learning a l…