Daniel Wontae Nam

13 papers A* 2Journal 7Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Binary Classifier Optimization for Large Language Model Alignment. ACL (1) Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, Kyoung-Woon On
2025	J	`jnl`	Kanana: Compute-efficient Bilingual Language Models. CoRR Yunju Bak, Hojin Lee, Minho Ryu, Jiyeon Ham, Seungjae Jung, Daniel Wontae Nam, Taegyeong Eo, Donghun Lee, Doohae Jung, Boseop Kim, Nayeon Kim, Jaesun Park, Hyunho Kim, Hyunwoong Ko, Changmin Lee, Kyoung-Woon On, Seulye Baeg, Junrae Cho, Sunghee Jung, Jieun Kang, EungGyun Kim, Eunhwa Kim, Byeongil Ko, Daniel Lee, Minchul Lee, Miok Lee, Shinbok Lee, Gaeun Seo
2024	J	`jnl`	Binary Classifier Optimization for Large Language Model Alignment. CoRR Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, Kyoung-Woon On
2024	—	`conf`	TLCR: Token-Level Continuous Reward for Fine-grained Reinforcement Learning from Human Feedback. ACL (Findings) Eunseop Yoon, Hee Suk Yoon, SooHwan Eom, Gunsoo Han, Daniel Wontae Nam, DaeJin Jo, Kyoung-Woon On, Mark Hasegawa-Johnson, Sungwoong Kim, Chang Dong Yoo
2024	J	`jnl`	TLCR: Token-Level Continuous Reward for Fine-grained Reinforcement Learning from Human Feedback. CoRR Eunseop Yoon, Hee Suk Yoon, SooHwan Eom, Gunsoo Han, Daniel Wontae Nam, DaeJin Jo, Kyoung-Woon On, Mark A. Hasegawa-Johnson, Sungwoong Kim, Chang D. Yoo
2023	—	`conf`	Efficient Latent Variable Modeling for Knowledge-Grounded Dialogue Generation. EMNLP (Findings) Gunsoo Han, DaeJin Jo, Daniel Wontae Nam, Eunseop Yoon, Taehwan Kwon, Seungeun Rho, Kyoung-Woon On, Chang Dong Yoo, Sungwoong Kim
2023	J	`jnl`	Effortless Integration of Memory Management into Open-Domain Conversation Systems. CoRR Eunbi Choi, Kyoung-Woon On, Gunsoo Han, Sungwoong Kim, Daniel Wontae Nam, DaeJin Jo, Seungeun Rho, Taehwan Kwon, Minjoon Seo
2023	J	`jnl`	Hexa: Self-Improving for Knowledge-Grounded Dialogue System. CoRR DaeJin Jo, Daniel Wontae Nam, Gunsoo Han, Kyoung-Woon On, Taehwan Kwon, Seungeun Rho, Sungwoong Kim
2022	A*	`conf`	LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward. NeurIPS DaeJin Jo, Sungwoong Kim, Daniel Wontae Nam, Taehwan Kwon, Seungeun Rho, Jongmin Kim, Donghoon Lee
2022	J	`jnl`	LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward. CoRR DaeJin Jo, Sungwoong Kim, Daniel Wontae Nam, Taehwan Kwon, Seungeun Rho, Jongmin Kim, Donghoon Lee
2021	A*	`conf`	GMAC: A Distributional Perspective on Actor-Critic Framework. ICML Daniel Wontae Nam, Younghoon Kim, Chan Y. Park
2021	J	`jnl`	GMAC: A Distributional Perspective on Actor-Critic Framework. CoRR Daniel Wontae Nam, Younghoon Kim, Chan Y. Park
2021	—	`conf`	Interactive Grounded Language Understanding in a Collaborative Environment: Retrospective on Iglu 2022 Competition. NeurIPS (Competition and Demos) Julia Kiseleva, Alexey Skrynnik, Artem Zholus, Shrestha Mohanty, Negar Arabzadeh, Marc-Alexandre Côté, Mohammad Aliannejadi, Milagro Teruel, Ziming Li, Mikhail Burtsev, Maartje ter Hoeve, Zoya Volovikova, Aleksandr Panov, Yuxuan Sun, Kavya Srinet, Arthur Szlam, Ahmed Awadallah, Seungeun Rho, Taehwan Kwon, Daniel Wontae Nam, Felipe Bivort Haiek, Edwin Zhang, Linar Abdrazakov, Guo Qingyam, Jason Zhang, Zhibin Guo

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.