What do they capture?

Author:

Wan Yao1,Zhao Wei1,Zhang Hongyu2,Sui Yulei3,Xu Guandong3,Jin Hai1

Affiliation:

1. Huazhong University of Science and Technology, China

2. University of Newcastle, Australia

3. University of Technology Sydney, Australia

Funder

National Natural Science Foundation of China

Publisher

ACM

Reference45 articles.

1. Uri Alon , Shaked Brody , Omer Levy , and Eran Yahav . 2018 . code2seq: Generating Sequences from Structured Representations of Code . In Proceedings of International Conference on Learning Representations. Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav. 2018. code2seq: Generating Sequences from Structured Representations of Code. In Proceedings of International Conference on Learning Representations.

2. code2vec: learning distributed representations of code

3. Empirical study of transformers for source code

4. Kevin Clark , Urvashi Khandelwal , Omer Levy , and Christopher D. Manning . 2019. What Does BERT Look at? An Analysis of BERT's Attention . In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. 276--286 . Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning. 2019. What Does BERT Look at? An Analysis of BERT's Attention. In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. 276--286.

5. Kevin Clark , Minh-Thang Luong , Quoc V. Le , and Christopher D. Manning . 2020. ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators . In Proceedings of International Conference on Learning Representations. Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020. ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. In Proceedings of International Conference on Learning Representations.

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