Pengcheng Yin

According to our database, Pengcheng Yin authored at least 53 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Land Cover Change Detection Based on Vector Polygons and Deep Learning With High-Resolution Remote Sensing Images.

Hui Zhang, Wei Liu, Hao Niu, Pengcheng Yin, Shiling Dong, Jialin Wu, Erzhu Li, Lianpeng Zhang, Changming Zhu

IEEE Trans. Geosci. Remote. Sens., 2024

A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond.

Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, Qipeng Guo, Xipeng Qiu, Pengcheng Yin, Xiaoli Li, Fei Yuan, Lingpeng Kong, Xiang Li, Zhiyong Wu

CoRR, 2024

Unsupervised Evaluation of Code LLMs with Round-Trip Correctness.

Miltiadis Allamanis, Sheena Panthaplackel, Pengcheng Yin

CoRR, 2024

Grounding Data Science Code Generation with Input-Output Specifications.

Yeming Wen, Pengcheng Yin, Kensen Shi, Henryk Michalewski, Swarat Chaudhuri, Alex Polozov

CoRR, 2024

2023

DIRE and its Data: Neural Decompiled Variable Renamings with Respect to Software Class.

Luke Dramko, Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Graham Neubig, Bogdan Vasilescu, Claire Le Goues

ACM Trans. Softw. Eng. Methodol., April, 2023

PaLM: Scaling Language Modeling with Pathways.

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel

J. Mach. Learn. Res., 2023

Universal Self-Consistency for Large Language Model Generation.

Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou

CoRR, 2023

L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models.

Ansong Ni, Pengcheng Yin, Yilun Zhao, Martin Riddell, Troy Feng, Rui Shen, Stephen Yin, Ye Liu, Semih Yavuz, Caiming Xiong, Shafiq Joty, Yingbo Zhou, Dragomir Radev, Arman Cohan

CoRR, 2023

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis.

Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton

CoRR, 2023

SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL.

Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister

CoRR, 2023

Can Large Language Models Reason about Program Invariants?

Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin

Proceedings of the International Conference on Machine Learning, 2023

SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data.

Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Natural Language to Code Generation in Interactive Data Science Notebooks.

Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Oleksandr Polozov, Charles Sutton

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization.

Ningyi Liao, Dingheng Mo, Siqiang Luo, Xiang Li, Pengcheng Yin

Proc. VLDB Endow., 2022

Compositional Generalization and Decomposition in Neural Program Synthesis.

Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton

CoRR, 2022

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.

Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data.

Shuyan Zhou, Li Zhang, Yue Yang, Qing Lyu, Pengcheng Yin, Chris Callison-Burch, Graham Neubig

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

On The Ingredients of an Effective Zero-shot Semantic Parser.

Pengcheng Yin, John Wieting, Avirup Sil, Graham Neubig

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Learning to Superoptimize Real-world Programs.

Alex Shypula, Pengcheng Yin, Jeremy Lacomis, Claire Le Goues, Edward J. Schwartz, Graham Neubig

CoRR, 2021

Hierarchical Control of Situated Agents through Natural Language.

Shuyan Zhou, Pengcheng Yin, Graham Neubig

CoRR, 2021

Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention.

Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Emmanouil Antonios Platanios, Yu Su, Sam Thomson, Jacob Andreas

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Learning Structural Edits via Incremental Tree Transformations.

Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig

Proceedings of the 9th International Conference on Learning Representations, 2021

LTE Device Identification Based on RF Fingerprint with Multi-Channel Convolutional Neural Network.

Pengcheng Yin, Linning Peng, Junqing Zhang, Ming Liu, Hua Fu, Aiqun Hu

Proceedings of the IEEE Global Communications Conference, 2021

2020

A Vertex Concavity-Convexity Detection Method for Three-Dimensional Spatial Objects Based on Geometric Algebra.

Pengcheng Yin, Ji-yi Zhang, Xiying Sun, Di Hu, Zhifeng Shi, Chengyan Wu

ISPRS Int. J. Geo Inf., 2020

PERQ: Predicting, Explaining, and Rectifying Failed Questions in KB-QA Systems.

Zhiyong Wu, Ben Kao, Tien-Hsuan Wu, Pengcheng Yin, Qun Liu

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data.

Pengcheng Yin, Graham Neubig, Wen-tau Yih, Sebastian Riedel

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Incorporating External Knowledge through Pre-training for Natural Language to Code Generation.

Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Merging Weak and Active Supervision for Semantic Parsing.

Ansong Ni, Pengcheng Yin, Graham Neubig

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Calculation for Multidimensional Topological Relations in 3D Cadastre Based on Geometric Algebra.

Zhifeng Shi, Di Hu, Pengcheng Yin, Chun Wang, Taisheng Chen, Ji-yi Zhang

ISPRS Int. J. Geo Inf., 2019

Small Manhole Cover Detection in Remote Sensing Imagery with Deep Convolutional Neural Networks.

Wei Liu, Dayu Cheng, Pengcheng Yin, Mengyuan Yang, Erzhu Li, Meng Xie, Lianpeng Zhang

ISPRS Int. J. Geo Inf., 2019

High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.

Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing

CoRR, 2019

DIRE: A Neural Approach to Decompiled Identifier Naming.

Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu

Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019

Learning to Represent Edits.

Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt

Proceedings of the 7th International Conference on Learning Representations, 2019

Reranking for Neural Semantic Parsing.

Pengcheng Yin, Graham Neubig

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Improving Open Information Extraction via Iterative Rank-Aware Learning.

Zhengbao Jiang, Pengcheng Yin, Graham Neubig

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Characteristics and Classification of Topological Spatial Relations in 3-D Cadasters.

Lili Fu, Pengcheng Yin, Gang Li, Zhifeng Shi, Youzhi Liu, Ji-yi Zhang

Inf., 2018

Remote sensing classification method of vegetation dynamics based on time series Landsat image: a case of opencast mining area in China.

Jiaxing Xu, Hua Zhao, Pengcheng Yin, Duo Jia, Gang Li

EURASIP J. Image Video Process., 2018

Learning to mine aligned code and natural language pairs from stack overflow.

Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig

Proceedings of the 15th International Conference on Mining Software Repositories, 2018

Learning to mine parallel natural language/source code corpora from stack overflow.

Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig

Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation.

Pengcheng Yin, Graham Neubig

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018

A Tree-based Decoder for Neural Machine Translation.

Xinyi Wang, Hieu Pham, Pengcheng Yin, Graham Neubig

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Retrieval-Based Neural Code Generation.

Shirley Anugrah Hayati, Raphaël Olivier, Pravalika Avvaru, Pengcheng Yin, Anthony Tomasic, Graham Neubig

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Towards Practical Open Knowledge Base Canonicalization.

Tien-Hsuan Wu, Zhiyong Wu, Ben Kao, Pengcheng Yin

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing.

Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

New Word Detection and Tagging on Chinese Twitter Stream.

Yuzhi Liang, Pengcheng Yin, Siu-Ming Yiu

Trans. Large Scale Data Knowl. Centered Syst., 2017

DyNet: The Dynamic Neural Network Toolkit.

Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, Pengcheng Yin

CoRR, 2017

Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML.

Xuezhe Ma, Pengcheng Yin, Jingzhou Liu, Graham Neubig, Eduard H. Hovy

CoRR, 2017

A Syntactic Neural Model for General-Purpose Code Generation.

Pengcheng Yin, Graham Neubig

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

3D Cadastral Data Model Based on Conformal Geometry Algebra.

Ji-yi Zhang, Pengcheng Yin, Gang Li, Hehe Gu, Hua Zhao, Jianchun Fu

ISPRS Int. J. Geo Inf., 2016

Neural Enquirer: Learning to Query Tables in Natural Language.

Pengcheng Yin, Zhengdong Lu, Hang Li, Ben Kao

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Neural Enquirer: Learning to Query Tables.

Pengcheng Yin, Zhengdong Lu, Hang Li, Ben Kao

CoRR, 2015

Answering Questions with Complex Semantic Constraints on Open Knowledge Bases.

Pengcheng Yin, Nan Duan, Ben Kao, Junwei Bao, Ming Zhou

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2013

Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs).

Zhouxi Wang, Pengcheng Yin, Joslynn S. Lee, Ramya Parasuram, Srinivas Somarowthu, Mary Jo Ondrechen

BMC Bioinform., 2013