Paiheng Xu - RankMe

23 papers A 1Journal 14Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Skill Discovery for Software Scripting Automation via Offline Simulations with LLMs. EACL (Findings) Paiheng Xu, Gang Wu, Xiang Chen, Tong Yu, Chang Xiao, Franck Dernoncourt, Tianyi Zhou, Wei Ai, Viswanathan (Vishy) Swaminathan
2025	—	`conf`	DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data. EMNLP (Findings) Yuhang Zhou, Jing Zhu, Shengyi Qian, Zhuokai Zhao, Xiyao Wang, Xiaoyu Liu, Ming Li, Paiheng Xu, Wei Ai, Furong Huang
2025	J	`jnl`	DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data. CoRR Yuhang Zhou, Jing Zhu, Shengyi Qian, Zhuokai Zhao, Xiyao Wang, Xiaoyu Liu, Ming Li, Paiheng Xu, Wei Ai, Furong Huang
2025	A	`conf`	Emojis Decoded: Leveraging ChatGPT for Enhanced Understanding in Social Media Communications. ICWSM Yuhang Zhou, Paiheng Xu, Xiyao Wang, Xuan Lu, Ge Gao, Wei Ai
2025	J	`jnl`	GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint. ACM Trans. Knowl. Discov. Data Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang
2025	—	`conf`	Large Language Models Struggle to Describe the Haystack without Human Help: A Social Science-Inspired Evaluation of Topic Models. ACL (1) Zongxia Li, Lorena Calvo-Bartolomé, Alexander Miserlis Hoyle, Paiheng Xu, Daniel Kofi Stephens, Juan Francisco Fung, Alden Dima, Jordan Lee Boyd-Graber
2025	J	`jnl`	Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of LLMs. CoRR Zongxia Li, Lorena Calvo-Bartolomé, Alexander Miserlis Hoyle, Paiheng Xu, Alden Dima, Juan Francisco Fung, Jordan L. Boyd-Graber
2025	—	`conf`	Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey. NAACL (Findings) Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, Yuhang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian J. McAuley, Wei Ai, Furong Huang
2025	J	`jnl`	Skill Discovery for Software Scripting Automation via Offline Simulations with LLMs. CoRR Paiheng Xu, Gang Wu, Xiang Chen, Tong Yu, Chang Xiao, Franck Dernoncourt, Tianyi Zhou, Wei Ai, Viswanathan (Vishy) Swaminathan
2024	J	`jnl`	Does Geo-co-location Matter? A Case Study of Public Health Conversations during COVID-19. CoRR Paiheng Xu, Louiqa Raschid, Vanessa Frías-Martínez
2024	J	`jnl`	Emojis Decoded: Leveraging ChatGPT for Enhanced Understanding in Social Media Communications. CoRR Yuhang Zhou, Paiheng Xu, Xiyao Wang, Xuan Lu, Ge Gao, Wei Ai
2024	—	`conf`	Explore Spurious Correlations at the Concept Level in Language Models for Text Classification. ACL (1) Yuhang Zhou, Paiheng Xu, Xiaoyu Liu, Bang An, Wei Ai, Furong Huang
2024	J	`jnl`	Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey. CoRR Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, Yuhang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian J. McAuley, Wei Ai, Furong Huang
2024	—	`conf`	Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. EMNLP (Findings) Yuhang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang
2024	J	`jnl`	Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. CoRR Yuhang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang
2024	—	`conf`	The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education. NAACL-HLT Paiheng Xu, Jing Liu, Nathan Jones, Julie Cohen, Wei Ai
2024	J	`jnl`	The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education. CoRR Paiheng Xu, Jing Liu, Nathan Jones, Julie Cohen, Wei Ai
2023	J	`jnl`	Explore Spurious Correlations at the Concept Level in Language Models for Text Classification. CoRR Yuhang Zhou, Paiheng Xu, Xiaoyu Liu, Bang An, Wei Ai, Furong Huang
2023	J	`jnl`	GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint. CoRR Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang
2023	J	`jnl`	Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps. CoRR Zongxia Li, Paiheng Xu, Fuxiao Liu, Hyemi Song
2021	—	`conf`	Using Noisy Self-Reports to Predict Twitter User Demographics. SocialNLP@NAACL Zach Wood-Doughty, Paiheng Xu, Xiao Liu, Mark Dredze
2020	J	`jnl`	The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets. CoRR Paiheng Xu, Mark Dredze, David A. Broniatowski
2020	J	`jnl`	Using Noisy Self-Reports to Predict Twitter User Demographics. CoRR Zach Wood-Doughty, Paiheng Xu, Xiao Liu, Mark Dredze

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.