Qiaozhi He - RankMe

24 papers A* 4Misc 1Journal 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	APR: Penalizing Structural Redundancy in Large Reasoning Models via Anchor-based Process Rewards. CoRR Kaiyan Chang, Chenwei Zhu, Yingfeng Luo, Yifu Huo, Chenglong Wang, Xiaoqian Liu, Qiaozhi He, Tong Xiao, Zhengtao Yu, Jingbo Zhu
2026	J	`jnl`	DaPT: A Dual-Path Framework for Multilingual Multi-hop Question Answering. CoRR Yilin Wang, Yuchun Fan, Jiaoyang Li, Ziming Zhu, Yongyu Mu, Qiaozhi He, Tong Xiao, Jingbo Zhu
2026	J	`jnl`	MSRL: Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning. CoRR Chenglong Wang, Yifu Huo, Yang Gan, Qiaozhi He, Qi Meng, Bei Li, Yan Wang, Junfu Liu, Tianhua Zhou, Jingbo Zhu, Tong Xiao
2026	A*	`conf`	Probing Preference Representations: A Multi-Dimensional Evaluation and Analysis Method for Reward Models. AAAI Chenglong Wang, Yifu Huo, Yang Gan, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Chunliang Zhang, Tongran Liu, Anxiang Ma, Zhengtao Yu, Jingbo Zhu, Tong Xiao
2026	J	`jnl`	SERM: Self-Evolving Relevance Model with Agent-Driven Learning from Massive Query Streams. CoRR Chenglong Wang, Canjia Li, Xingzhao Zhu, Yifu Huo, Huiyu Wang, Weixiong Lin, Yun Yang, Qiaozhi He, Tianhua Zhou, Xiaojia Chang, Jingbo Zhu, Tong Xiao
2026	J	`jnl`	When Scaling Fails: Mitigating Audio Perception Decay of LALMs via Multi-Step Perception-Aware Reasoning. CoRR Ruixiang Mao, Xiangnan Ma, Dan Chen, Ziming Zhu, Yuan Ge, Aokai Hao, Haishu Zhao, Yifu Huo, Qing Yang, Kaiyan Chang, Xiaoqian Liu, Chenglong Wang, Qiaozhi He, Tong Xiao, Jingbo Zhu
2025	Misc	`conf`	Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal Models. ICASSP Yongyu Mu, Hengyu Li, Junxin Wang, Xiaoxuan Zhou, Chenglong Wang, Yingfeng Luo, Qiaozhi He, Tong Xiao, Guocheng Chen, Jingbo Zhu
2025	J	`jnl`	Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal Models. CoRR Yongyu Mu, Hengyu Li, Junxin Wang, Xiaoxuan Zhou, Chenglong Wang, Yingfeng Luo, Qiaozhi He, Tong Xiao, Guocheng Chen, Jingbo Zhu
2025	A*	`conf`	GRAM: A Generative Foundation Reward Model for Reward Generalization. ICML Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu
2025	J	`jnl`	GRAM: A Generative Foundation Reward Model for Reward Generalization. CoRR Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu
2025	J	`jnl`	Probing Preference Representations: A Multi-Dimensional Evaluation and Analysis Method for Reward Models. CoRR Chenglong Wang, Yifu Huo, Yang Gan, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Chunliang Zhang, Tongran Liu, Anxiang Ma, Zhengtao Yu, Jingbo Zhu, Tong Xiao
2025	A*	`conf`	RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data. AAAI Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Murun Yang, Qiaozhi He, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu
2025	A*	`conf`	StickMotion: Generating 3D Human Motions by Drawing a Stickman. CVPR Tao Wang, Zhihua Wu, Qiaozhi He, Jiaming Chu, Ling Qian, Yu Cheng, Junliang Xing, Jian Zhao, Lei Jin
2025	J	`jnl`	StickMotion: Generating 3D Human Motions by Drawing a Stickman. CoRR Tao Wang, Zhihua Wu, Qiaozhi He, Jiaming Chu, Ling Qian, Yu Cheng, Junliang Xing, Jian Zhao, Lei Jin
2024	J	`jnl`	ChuXin: 1.6B Technical Report. CoRR Xiaomin Zhuang, Yufan Jiang, Qiaozhi He, Zhihua Wu
2024	J	`jnl`	Code Comparison Tuning for Code Large Language Models. CoRR Yufan Jiang, Qiaozhi He, Xiaomin Zhuang, Zhihua Wu
2024	J	`jnl`	Cross-layer Attention Sharing for Large Language Models. CoRR Yongyu Mu, Yuzhang Wu, Yuchun Fan, Chenglong Wang, Hengyu Li, Qiaozhi He, Murun Yang, Tong Xiao, Jingbo Zhu
2024	J	`jnl`	Efficient LLM Inference with Kcache. CoRR Qiaozhi He, Zhihua Wu
2024	J	`jnl`	Exploring Scaling Laws for Local SGD in Large Language Model Training. CoRR Qiaozhi He, Xiaomin Zhuang, Zhihua Wu
2024	J	`jnl`	LRHP: Learning Representations for Human Preferences via Preference Pairs. CoRR Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu
2024	J	`jnl`	RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data. CoRR Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Murun Yang, Qiaozhi He, Tong Xiao, Chunliang Zhang, Tongran Liu, Quan Du, Di Yang, Jingbo Zhu
2023	J	`jnl`	Learning Reliable Neural Networks with Distributed Architecture Representations. ACM Trans. Asian Low Resour. Lang. Inf. Process. Yinqiao Li, Runzhe Cao, Qiaozhi He, Tong Xiao, Jingbo Zhu
2023	J	`jnl`	RecycleGPT: An Autoregressive Language Model with Recyclable Module. CoRR Yufan Jiang, Qiaozhi He, Xiaomin Zhuang, Zhihua Wu, Kunpeng Wang, Wenlai Zhao, Guangwen Yang
2018	J	`jnl`	Research on the Temperature Characteristics of the Photoacoustic Sensor of Glucose Solution. Sensors Wei Tao, Zhiqian Lu, Qiaozhi He, Pengfei Lv, Qian Wang, Hui Zhao

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.