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2020 – today
- 2024
[j13]Hui Zhang
, Wei Liu, Hao Niu, Pengcheng Yin, Shiling Dong, Jialin Wu, Erzhu Li, Lianpeng Zhang, Changming Zhu:
Land Cover Change Detection Based on Vector Polygons and Deep Learning With High-Resolution Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 62: 1-18 (2024)- [j12]Ningyi Liao, Dingheng Mo, Siqiang Luo, Xiang Li, Pengcheng Yin:
Scalable decoupling graph neural network with feature-oriented optimization. VLDB J. 33(3): 667-683 (2024) - [c31]Kensen Shi, Joey Hong, Yinlin Deng, Pengcheng Yin, Manzil Zaheer, Charles Sutton:
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. ICLR 2024 - [c30]Miltiadis Allamanis, Sheena Panthaplackel, Pengcheng Yin:
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness. ICML 2024 - [c29]Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, Pengcheng Yin:
NExT: Teaching Large Language Models to Reason about Code Execution. ICML 2024 - [i38]Yeming Wen, Pengcheng Yin, Kensen Shi, Henryk Michalewski, Swarat Chaudhuri, Alex Polozov:
Grounding Data Science Code Generation with Input-Output Specifications. CoRR abs/2402.08073 (2024) - [i37]Miltiadis Allamanis, Sheena Panthaplackel, Pengcheng Yin:
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness. CoRR abs/2402.08699 (2024) - [i36]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:
A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond. CoRR abs/2403.14734 (2024) - [i35]Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, Pengcheng Yin:
NExT: Teaching Large Language Models to Reason about Code Execution. CoRR abs/2404.14662 (2024) - [i34]Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans:
UQE: A Query Engine for Unstructured Databases. CoRR abs/2407.09522 (2024) - [i33]Ruisheng Cao, Fangyu Lei, Haoyuan Wu, Jixuan Chen, Yeqiao Fu, Hongcheng Gao, Xinzhuang Xiong, Hanchong Zhang, Yuchen Mao, Wenjing Hu, Tianbao Xie, Hongshen Xu, Danyang Zhang, Sida Wang, Ruoxi Sun, Pengcheng Yin, Caiming Xiong, Ansong Ni, Qian Liu, Victor Zhong, Lu Chen, Kai Yu, Tao Yu:
Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows? CoRR abs/2407.10956 (2024) - [i32]Kensen Shi, Deniz Altinbüken, Saswat Anand, Mihai Christodorescu, Katja Grünwedel, Alexa Koenings, Sai Naidu, Anurag Pathak, Marc Rasi, Fredde Ribeiro, Brandon Ruffin, Siddhant Sanyam, Maxim Tabachnyk, Sara Toth, Roy Tu, Tobias Welp, Pengcheng Yin, Manzil Zaheer, Satish Chandra, Charles Sutton:
Natural Language Outlines for Code: Literate Programming in the LLM Era. CoRR abs/2408.04820 (2024) - 2023
- [j11]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:
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24: 240:1-240:113 (2023) - [j10]Luke Dramko, Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Graham Neubig, Bogdan Vasilescu, Claire Le Goues:
DIRE and its Data: Neural Decompiled Variable Renamings with Respect to Software Class. ACM Trans. Softw. Eng. Methodol. 32(2): 39:1-39:34 (2023) - [c28]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:
Natural Language to Code Generation in Interactive Data Science Notebooks. ACL (1) 2023: 126-173 - [c27]Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister:
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. EMNLP (Findings) 2023: 542-550 - [c26]Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin:
Can Large Language Models Reason about Program Invariants? ICML 2023: 27496-27520 - [i31]Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister:
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL. CoRR abs/2306.00739 (2023) - [i30]Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton:
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. CoRR abs/2307.13883 (2023) - [i29]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:
L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models. CoRR abs/2309.17446 (2023) - [i28]Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister:
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. CoRR abs/2311.02883 (2023) - [i27]Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou:
Universal Self-Consistency for Large Language Model Generation. CoRR abs/2311.17311 (2023) - 2022
- [j9]Ningyi Liao, Dingheng Mo, Siqiang Luo, Xiang Li, Pengcheng Yin:
SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization. Proc. VLDB Endow. 15(11): 3240-3248 (2022) - [c25]Pengcheng Yin, John Wieting, Avirup Sil, Graham Neubig:
On The Ingredients of an Effective Zero-shot Semantic Parser. ACL (1) 2022: 1455-1474 - [c24]Shuyan Zhou, Li Zhang, Yue Yang, Qing Lyu, Pengcheng Yin, Chris Callison-Burch, Graham Neubig:
Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data. ACL (1) 2022: 2998-3012 - [c23]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:
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. EMNLP 2022: 602-631 - [i26]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 R. Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. CoRR abs/2201.05966 (2022) - [i25]Shuyan Zhou, Li Zhang, Yue Yang, Qing Lyu, Pengcheng Yin, Chris Callison-Burch, Graham Neubig:
Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data. CoRR abs/2203.07264 (2022) - [i24]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:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - [i23]Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton:
Compositional Generalization and Decomposition in Neural Program Synthesis. CoRR abs/2204.03758 (2022) - [i22]Ningyi Liao, Dingheng Mo, Siqiang Luo, Xiang Li, Pengcheng Yin:
SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization. CoRR abs/2207.09179 (2022) - [i21]Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Alex Polozov, Charles Sutton:
Natural Language to Code Generation in Interactive Data Science Notebooks. CoRR abs/2212.09248 (2022) - 2021
- [c22]Pengcheng Yin, Linning Peng, Junqing Zhang, Ming Liu, Hua Fu, Aiqun Hu:
LTE Device Identification Based on RF Fingerprint with Multi-Channel Convolutional Neural Network. GLOBECOM 2021: 1-6 - [c21]Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig:
Learning Structural Edits via Incremental Tree Transformations. ICLR 2021 - [c20]Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Emmanouil Antonios Platanios, Yu Su, Sam Thomson, Jacob Andreas:
Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention. NAACL-HLT 2021: 2810-2823 - [i20]Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig:
Learning Structural Edits via Incremental Tree Transformations. CoRR abs/2101.12087 (2021) - [i19]Shuyan Zhou, Pengcheng Yin, Graham Neubig:
Hierarchical Control of Situated Agents through Natural Language. CoRR abs/2109.08214 (2021) - [i18]Alex Shypula, Pengcheng Yin, Jeremy Lacomis, Claire Le Goues, Edward J. Schwartz, Graham Neubig:
Learning to Superoptimize Real-world Programs. CoRR abs/2109.13498 (2021) - [i17]Pengcheng Yin, John Wieting, Avirup Sil, Graham Neubig:
On The Ingredients of an Effective Zero-shot Semantic Parser. CoRR abs/2110.08381 (2021) - 2020
- [j8]Pengcheng Yin, Ji-yi Zhang, Xiying Sun, Di Hu, Zhifeng Shi, Chengyan Wu:
A Vertex Concavity-Convexity Detection Method for Three-Dimensional Spatial Objects Based on Geometric Algebra. ISPRS Int. J. Geo Inf. 9(1): 25 (2020) - [c19]Ansong Ni, Pengcheng Yin, Graham Neubig:
Merging Weak and Active Supervision for Semantic Parsing. AAAI 2020: 8536-8543 - [c18]Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig:
Incorporating External Knowledge through Pre-training for Natural Language to Code Generation. ACL 2020: 6045-6052 - [c17]Pengcheng Yin, Graham Neubig, Wen-tau Yih, Sebastian Riedel:
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data. ACL 2020: 8413-8426 - [c16]Zhiyong Wu, Ben Kao, Tien-Hsuan Wu, Pengcheng Yin, Qun Liu:
PERQ: Predicting, Explaining, and Rectifying Failed Questions in KB-QA Systems. WSDM 2020: 663-671 - [i16]Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig:
Incorporating External Knowledge through Pre-training for Natural Language to Code Generation. CoRR abs/2004.09015 (2020) - [i15]Pengcheng Yin, Graham Neubig, Wen-tau Yih, Sebastian Riedel:
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data. CoRR abs/2005.08314 (2020)
2010 – 2019
- 2019
- [j7]Wei Liu, Dayu Cheng, Pengcheng Yin, Mengyuan Yang, Erzhu Li, Meng Xie, Lianpeng Zhang:
Small Manhole Cover Detection in Remote Sensing Imagery with Deep Convolutional Neural Networks. ISPRS Int. J. Geo Inf. 8(1): 49 (2019) - [j6]Zhifeng Shi, Di Hu, Pengcheng Yin, Chun Wang, Taisheng Chen, Ji-yi Zhang:
Calculation for Multidimensional Topological Relations in 3D Cadastre Based on Geometric Algebra. ISPRS Int. J. Geo Inf. 8(11): 469 (2019) - [c15]Pengcheng Yin, Graham Neubig:
Reranking for Neural Semantic Parsing. ACL (1) 2019: 4553-4559 - [c14]Zhengbao Jiang, Pengcheng Yin, Graham Neubig:
Improving Open Information Extraction via Iterative Rank-Aware Learning. ACL (1) 2019: 5295-5300 - [c13]Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt:
Learning to Represent Edits. ICLR (Poster) 2019 - [c12]Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu:
DIRE: A Neural Approach to Decompiled Identifier Naming. ASE 2019: 628-639 - [i14]Zhengbao Jiang, Pengcheng Yin, Graham Neubig:
Improving Open Information Extraction via Iterative Rank-Aware Learning. CoRR abs/1905.13413 (2019) - [i13]Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing:
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CoRR abs/1905.13545 (2019) - [i12]Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu:
DIRE: A Neural Approach to Decompiled Identifier Naming. CoRR abs/1909.09029 (2019) - [i11]Ansong Ni, Pengcheng Yin, Graham Neubig:
Merging Weak and Active Supervision for Semantic Parsing. CoRR abs/1911.12986 (2019) - 2018
- [j5]Jiaxing Xu, Hua Zhao, Pengcheng Yin, Duo Jia, Gang Li:
Remote sensing classification method of vegetation dynamics based on time series Landsat image: a case of opencast mining area in China. EURASIP J. Image Video Process. 2018: 113 (2018) - [j4]Lili Fu, Pengcheng Yin, Gang Li, Zhifeng Shi, Youzhi Liu, Ji-yi Zhang:
Characteristics and Classification of Topological Spatial Relations in 3-D Cadasters. Inf. 9(4): 71 (2018) - [c11]Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig:
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. ACL (1) 2018: 754-765 - [c10]Tien-Hsuan Wu, Zhiyong Wu, Ben Kao, Pengcheng Yin:
Towards Practical Open Knowledge Base Canonicalization. CIKM 2018: 883-892 - [c9]Pengcheng Yin, Graham Neubig:
TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation. EMNLP (Demonstration) 2018: 7-12 - [c8]Shirley Anugrah Hayati, Raphaël Olivier, Pravalika Avvaru, Pengcheng Yin, Anthony Tomasic, Graham Neubig:
Retrieval-Based Neural Code Generation. EMNLP 2018: 925-930 - [c7]Xinyi Wang, Hieu Pham, Pengcheng Yin, Graham Neubig:
A Tree-based Decoder for Neural Machine Translation. EMNLP 2018: 4772-4777 - [c6]Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig:
Learning to mine parallel natural language/source code corpora from stack overflow. ICSE (Companion Volume) 2018: 388-389 - [c5]Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig:
Learning to mine aligned code and natural language pairs from stack overflow. MSR 2018: 476-486 - [i10]Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig:
Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow. CoRR abs/1805.08949 (2018) - [i9]Pengcheng Yin, Chunting Zhou, Junxian He, Graham Neubig:
StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing. CoRR abs/1806.07832 (2018) - [i8]Xinyi Wang, Hieu Pham, Pengcheng Yin, Graham Neubig:
A Tree-based Decoder for Neural Machine Translation. CoRR abs/1808.09374 (2018) - [i7]Shirley Anugrah Hayati, Raphaël Olivier, Pravalika Avvaru, Pengcheng Yin, Anthony Tomasic, Graham Neubig:
Retrieval-Based Neural Code Generation. CoRR abs/1808.10025 (2018) - [i6]Pengcheng Yin, Graham Neubig:
TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation. CoRR abs/1810.02720 (2018) - [i5]Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt:
Learning to Represent Edits. CoRR abs/1810.13337 (2018) - 2017
- [j3]Yuzhi Liang, Pengcheng Yin, Siu-Ming Yiu:
New Word Detection and Tagging on Chinese Twitter Stream. Trans. Large Scale Data Knowl. Centered Syst. 32: 69-90 (2017) - [c4]Pengcheng Yin, Graham Neubig:
A Syntactic Neural Model for General-Purpose Code Generation. ACL (1) 2017: 440-450 - [i4]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:
DyNet: The Dynamic Neural Network Toolkit. CoRR abs/1701.03980 (2017) - [i3]Pengcheng Yin, Graham Neubig:
A Syntactic Neural Model for General-Purpose Code Generation. CoRR abs/1704.01696 (2017) - [i2]Xuezhe Ma, Pengcheng Yin, Jingzhou Liu, Graham Neubig, Eduard H. Hovy:
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML. CoRR abs/1705.07136 (2017) - 2016
- [j2]Ji-yi Zhang, Pengcheng Yin, Gang Li, Hehe Gu, Hua Zhao, Jianchun Fu:
3D Cadastral Data Model Based on Conformal Geometry Algebra. ISPRS Int. J. Geo Inf. 5(2): 20 (2016) - [c3]Pengcheng Yin, Zhengdong Lu, Hang Li, Ben Kao:
Neural Enquirer: Learning to Query Tables in Natural Language. IJCAI 2016: 2308-2314 - 2015
- [c2]Pengcheng Yin, Nan Duan, Ben Kao, Junwei Bao, Ming Zhou:
Answering Questions with Complex Semantic Constraints on Open Knowledge Bases. CIKM 2015: 1301-1310 - [c1]Yuzhi Liang, Pengcheng Yin, Siu-Ming Yiu:
New Word Detection and Tagging on Chinese Twitter Stream. DaWaK 2015: 310-321 - [i1]Pengcheng Yin, Zhengdong Lu, Hang Li, Ben Kao:
Neural Enquirer: Learning to Query Tables. CoRR abs/1512.00965 (2015) - 2013
- [j1]Zhouxi Wang, Pengcheng Yin, Joslynn S. Lee, Ramya Parasuram, Srinivas Somarowthu, Mary Jo Ondrechen:
Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs). BMC Bioinform. 14(S-3): S13 (2013)
Coauthor Index
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