Leonard Lausen

23 papers A* 3C 1Misc 1Journal 13Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Connecting the Impact of Silent Data Corruption With Different Training Characteristics: An Empirical Study. IEEE Micro Hengzhi Pei, Leonard Lausen, George Karypis
2025	—	`conf`	Understanding Silent Data Corruption in LLM Training. ACL (1) Jeffrey Jian Ma, Hengzhi Pei, Leonard Lausen, George Karypis
2025	J	`jnl`	Understanding Silent Data Corruption in LLM Training. CoRR Jeffrey Jian Ma, Hengzhi Pei, Leonard Lausen, George Karypis
2025	C	`conf`	When Silicon Fails Silently: Characterizing Hardware-Induced Corruption in LLM Training. IOLTS Jeffrey Jian Ma, Hengzhi Pei, Leonard Lausen, George Karypis
2024	—	`conf`	Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. ENLSP Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Thomas Brox, Sheng Zha, George Karypis
2024	J	`jnl`	Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. CoRR Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Sheng Zha, Thomas Brox, George Karypis
2023	A*	`conf`	Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
2023	A*	`conf`	HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
2023	A*	`conf`	Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks. CoRR Soumajyoti Sarkar, Leonard Lausen
2022	—	`conf`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	J	`jnl`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	J	`jnl`	Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic. CoRR Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, Leonard Lausen, Sheng Zha, Saab Mansour
2020	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 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
2019	—	`conf`	Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
2019	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR 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
2017	—	`conf`	Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. NIPS Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2017	J	`jnl`	Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. CoRR Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2017	J	`jnl`	NSML: A Machine Learning Platform That Enables You to Focus on Your Models. CoRR Nako Sung, Minkyu Kim, Hyunwoo Jo, Youngil Yang, Jingwoong Kim, Leonard Lausen, Youngkwan Kim, Gayoung Lee, Dong-Hyun Kwak, Jung-Woo Ha, Sunghun Kim
2016	Misc	`conf`	CrowdRisk: exploring crowdsourcing of risk information. OZCHI Leonard Lausen, Markus Rittenbruch, Peta Mitchell, Ella Horton, Marcus Foth

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.