Leonard Lausen

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 17

Top Topics

Natural Language

Data Representation

Top Venues

EMNLP/IJCNLP (2)

Publications

Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI (2023)
Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS (2023)
Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR (2023)
Soumajyoti Sarkar, Leonard Lausen
Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks. CoRR (2023)
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS (2023)
Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR (2023)
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR (2023)
Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, Leonard Lausen, Sheng Zha, Saab Mansour
Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic. CoRR (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR (2022)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 21 (2020)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR (2019)
Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) (2019)
Nako Sung, Minkyu Kim, Hyunwoo Jo, Youngil Yang, Jingwoong Kim, Leonard Lausen, Youngkwan Kim, Gayoung Lee, Dong-Hyun Kwak, Jung-Woo Ha, Sunghun Kim
NSML: A Machine Learning Platform That Enables You to Focus on Your Models. CoRR (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. NIPS (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. CoRR (2017)
Leonard Lausen, Markus Rittenbruch, Peta Mitchell, Ella Horton, Marcus Foth
CrowdRisk: exploring crowdsourcing of risk information. OZCHI (2016)