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Smart contract code summarization is crucial for efficient maintenance and vulnerability mitigation.
Codesearchnet challenge: Evaluating the state of semantic code search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019 · 1909
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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CodeBERT: A pre-trained model for programming and natural languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. 2020 · 2020
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Making monolingual sentence embeddings multilingual using knowledge distillation
Nils Reimers and Iryna Gurevych. 2020 · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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Understanding code reuse in smart contracts
Xiangping Chen, Peiyong Liao, Yixin Zhang, Yuan Huang, and Zibin Zheng. 2021 · 2021
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Smart contract vulnerability detection: From pure neural network to interpretable graph feature and expert pattern fusion
Zhenguang Liu, Peng Qian, Xiang Wang, Lei Zhu, Qinming He, and Shouling Ji. 2021 · 2021
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Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation
Yue Wang, Weishi Wang, Shafiq Joty, and Steven C.H. Hoi. 2021 · 2021
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A multi-modal transformer-based code summarization approach for smart contracts
Zhen Yang, Jacky Keung, Xiao Yu, Xiaodong Gu, Zhengyuan Wei, Xiaoxue Ma, and Miao Zhang. 2021 · 2021
Cited alongside, same era.
Multilingual training for software engineering
Toufique Ahmed and Premkumar Devanbu. 2022 · 2022
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A continual learning survey: Defying forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Aleš Leonardis, Gregory Slabaugh, and Tinne Tuytelaars. 2022 · 2022
Cited alongside, same era.
Few-shot training llms for project-specific code-summarization
Toufique Ahmed and Premkumar Devanbu. 2023 · 2023
Later among the works it cites.
Smartstate: Detecting state-reverting vulnerabilities in smart contracts via fine-grained state-dependency analysis
Zeqin Liao, Sicheng Hao, Yuhong Nan, and Zibin Zheng. 2023 · 2023
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CodeT5+: Open code large language models for code understanding and generation
Yue Wang, Hung Le, Akhilesh Gotmare, Nghi Bui, Junnan Li, and Steven Hoi. 2023 · 2023
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Automatic semantic augmentation of language model prompts (for code summarization)
Toufique Ahmed, Kunal Suresh Pai, Premkumar Devanbu, and Earl Barr. 2024 · 2024
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