35 citations · 114 across the 31 of their papers we have counts for
10 papers · 1 filter
Mitigating Negative Style Transfer in Hybrid Dialogue System
Shimin Li, Qinyuan Cheng, Linyang Li +1
As the functionality of dialogue systems evolves, hybrid dialogue systems that accomplish user-specific goals and participate in open-topic chitchat with users are attracting growi…
Investigating Glyph Phonetic Information for Chinese Spell Checking: What Works and What's Next
Xiaotian Zhang, Yanjun Zheng, Hang Yan +1
While pre-trained Chinese language models have demonstrated impressive performance on a wide range of NLP tasks, the Chinese Spell Checking (CSC) task remains a challenge. Previous…
Word-Level Representation From Bytes For Language Modeling
Chu-Tak Lee, Qipeng Guo, Xipeng Qiu
Modern language models mostly take sub-words as input, a design that balances the trade-off between vocabulary size, number of parameters, and performance. However, sub-word tokeni…
DORE: Document Ordered Relation Extraction based on Generative Framework
Qipeng Guo, Yuqing Yang, Hang Yan +2
In recent years, there is a surge of generation-based information extraction work, which allows a more direct use of pre-trained language models and efficiently captures output dep…
SDCL: Self-Distillation Contrastive Learning for Chinese Spell Checking
Xiaotian Zhang, Hang Yan, Yu Sun +1
Due to the ambiguity of homophones, Chinese Spell Checking (CSC) has widespread applications. Existing systems typically utilize BERT for text encoding. However, CSC requires the m…
RLET: A Reinforcement Learning Based Approach for Explainable QA with Entailment Trees
Tengxiao Liu, Qipeng Guo, Xiangkun Hu +3
Interpreting the reasoning process from questions to answers poses a challenge in approaching explainable QA. A recently proposed structured reasoning format, entailment tree, mana…
Soft-Labeled Contrastive Pre-training for Function-level Code Representation
Xiaonan Li, Daya Guo, Yeyun Gong +6
Code contrastive pre-training has recently achieved significant progress on code-related tasks. In this paper, we present \textbf{SCodeR}, a \textbf{S}oft-labeled contrastive pre-t…
Multitask Pre-training of Modular Prompt for Chinese Few-Shot Learning
Tianxiang Sun, Zhengfu He, Qin Zhu +2
Prompt tuning is a parameter-efficient approach to adapting pre-trained language models to downstream tasks. Although prompt tuning has been shown to match the performance of full…
Text Adversarial Purification as Defense against Adversarial Attacks
Linyang Li, Demin Song, Xipeng Qiu
Adversarial purification is a successful defense mechanism against adversarial attacks without requiring knowledge of the form of the incoming attack. Generally, adversarial purifi…
CodeRetriever: Unimodal and Bimodal Contrastive Learning for Code Search
Xiaonan Li, Yeyun Gong, Yelong Shen +7
In this paper, we propose the CodeRetriever model, which learns the function-level code semantic representations through large-scale code-text contrastive pre-training. We adopt tw…