Papers by Zhangyin Feng
Exploring and Adapting Chinese GPT to Pinyin Input Method (2022.acl-long)
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| Challenge: | a frozen GPT can generate state-of-the-art performance on perfect pinyin, but performance drops when input includes abbreviated pinyan, which links to even larger number of Chinese characters. |
| Approach: | They propose to use Chinese GPT to generate fluent sentences using abbreviated pinyin. |
| Outcome: | The proposed approach improves on abbreviated pinyin across all domains. |
Improved Visual Story Generation with Adaptive Context Modeling (2023.findings-acl)
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| Challenge: | a recent work shows that diffusion models generate images of high resolution and semantic consistency to text prompts. |
| Approach: | They propose a method that uses adaptive context modeling to improve leading system . they evaluate their method on pororoSV and FlintstonesSV datasets . |
| Outcome: | The proposed method achieves state-of-the-art FID scores on pororo and Flintstones datasets. |
CodeBERT: A Pre-Trained Model for Programming and Natural Languages (2020.findings-emnlp)
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Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, Ming Zhou
| Challenge: | Large pre-trained models have improved performance on a variety of natural language processing tasks. |
| Approach: | They develop a bimodal pre-trained model for programming language (PL) and natural language (NL) it incorporates a hybrid objective function that detects replaced tokens from generators. |
| Outcome: | The proposed model performs better on two NL-PL applications by fine-tuning model parameters. |
LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network (2020.acl-main)
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Wanjun Zhong, Duyu Tang, Zhangyin Feng, Nan Duan, Ming Zhou, Ming Gong, Linjun Shou, Daxin Jiang, Jiahai Wang, Jian Yin
| Challenge: | Existing methods for fact checking textual statements are not yet available. |
| Approach: | They propose a neural network approach capable of leveraging logical operations for fact checking . they use a textual statement and semi-structured tables to generate a program from it . |
| Outcome: | The proposed approach achieves state-of-the-art performance on TABFACT dataset . it derives a program (a.k.a. logical form) of the statement in semantic parsing manner . |
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction (2022.findings-acl)
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| Challenge: | a Chinese model with whole word masking has no subword because each token is an atomic character. |
| Approach: | They propose to use whole word masking to mask all subwords corresponding to a word at once . they ask models to revise or insert tokens in a masked language modeling manner . |
| Outcome: | The proposed model performs better when one character is inserted or replaced . the model trained with standard character-level masking performs best when one token is masked . |