Zhaolin Gao - RankMe

17 papers A* 6A 1Journal 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating RL for LLM Reasoning with Optimal Advantage Regression. CoRR Kianté Brantley, Mingyu Chen, Zhaolin Gao, Jason D. Lee, Wen Sun, Wenhao Zhan, Xuezhou Zhang
2025	A	`conf`	LangPTune: Optimizing Language-based User Profiles for Recommendation. CIKM Zhaolin Gao, Joyce Zhou, Yijia Dai, Thorsten Joachims
2025	J	`jnl`	Pre-trained Large Language Models Learn Hidden Markov Models In-context. CoRR Yijia Dai, Zhaolin Gao, Yahya Sattar, Sarah Dean, Jennifer J. Sun
2025	J	`jnl`	Prompt Curriculum Learning for Efficient LLM Post-Training. CoRR Zhaolin Gao, Joongwon Kim, Wen Sun, Thorsten Joachims, Sid Wang, Richard Yuanzhe Pang, Liang Tan
2025	J	`jnl`	Q♯: Provably Optimal Distributional RL for LLM Post-Training. CoRR Jin Peng Zhou, Kaiwen Wang, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kilian Q. Weinberger, Kianté Brantley, Wen Sun
2025	A*	`conf`	Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. ICLR Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun
2025	J	`jnl`	Value-Guided Search for Efficient Chain-of-Thought Reasoning. CoRR Kaiwen Wang, Jin Peng Zhou, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kianté Brantley, Wen Sun
2024	J	`jnl`	End-to-end Training for Recommendation with Language-based User Profiles. CoRR Zhaolin Gao, Joyce Zhou, Yijia Dai, Thorsten Joachims
2024	A*	`conf`	REBEL: Reinforcement Learning via Regressing Relative Rewards. NeurIPS Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	REBEL: Reinforcement Learning via Regressing Relative Rewards. CoRR Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. CoRR Zhaolin Gao, Wenhao Zhan, Jonathan D. Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun
2024	J	`jnl`	Reviewer2: Optimizing Review Generation Through Prompt Generation. CoRR Zhaolin Gao, Kianté Brantley, Thorsten Joachims
2022	A*	`conf`	MCL: Mixed-Centric Loss for Collaborative Filtering. WWW Zhaolin Gao, Zhaoyue Cheng, Felipe Pérez, Jianing Sun, Maksims Volkovs
2022	A*	`conf`	Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems. SIGIR Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner
2020	A*	`conf`	Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks. INFOCOM Wanyu Lin, Zhaolin Gao, Baochun Li
2020	A*	`conf`	Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data. CVPR Wanyu Lin, Zhaolin Gao, Baochun Li
2019	J	`jnl`	Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data. CoRR Wanyu Lin, Zhaolin Gao, Baochun Li

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.