Sam Toyer - RankMe

25 papers A* 4B 1Misc 1Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs. CoRR Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu, Christopher A. Choquette-Choo, Stephanie Lin, Nikhil Kandpal, Milad Nasr, Rai, Sam Toyer, Miles Wang, Yaodong Yu, Alex Beutel, Kai Xiao
2025	J	`jnl`	Trading Inference-Time Compute for Adversarial Robustness. CoRR Wojciech Zaremba, Evgenia Nitishinskaya, Boaz Barak, Stephanie Lin, Sam Toyer, Yaodong Yu, Rachel Dias, Eric Wallace, Kai Xiao, Johannes Heidecke, Amelia Glaese
2024	A*	`conf`	A StrongREJECT for Empty Jailbreaks. NeurIPS Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer
2024	J	`jnl`	A StrongREJECT for Empty Jailbreaks. CoRR Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer
2024	J	`jnl`	Deliberative Alignment: Reasoning Enables Safer Language Models. CoRR Melody Y. Guan, Manas Joglekar, Eric Wallace, Saachi Jain, Boaz Barak, Alec Helyar, Rachel Dias, Andrea Vallone, Hongyu Ren, Jason Wei, Hyung Won Chung, Sam Toyer, Johannes Heidecke, Alex Beutel, Amelia Glaese
2024	J	`jnl`	Exploring and Addressing Reward Confusion in Offline Preference Learning. CoRR Xin Chen, Sam Toyer, Florian Shkurti
2024	J	`jnl`	Human Action Anticipation: A Survey. CoRR Bolin Lai, Sam Toyer, Tushar Nagarajan, Rohit Girdhar, Shengxin Zha, James M. Rehg, Kris Kitani, Kristen Grauman, Ruta Desai, Miao Liu
2024	A*	`conf`	Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. ICLR Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell
2023	J	`jnl`	Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. CoRR Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell
2022	J	`jnl`	A Primer on Maximum Causal Entropy Inverse Reinforcement Learning. CoRR Adam Gleave, Sam Toyer
2022	J	`jnl`	An Empirical Investigation of Representation Learning for Imitation. CoRR Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2022	J	`jnl`	imitation: Clean Imitation Learning Implementations. CoRR Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell
2021	—	`conf`	An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2020	J	`jnl`	ASNets: Deep Learning for Generalised Planning. J. Artif. Intell. Res. Sam Toyer, Sylvie Thiébaux, Felipe W. Trevizan, Lexing Xie
2020	J	`jnl`	DERAIL: Diagnostic Environments for Reward And Imitation Learning. CoRR Pedro Freire, Adam Gleave, Sam Toyer, Stuart Russell
2020	A*	`conf`	The MAGICAL Benchmark for Robust Imitation. NeurIPS Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell
2020	J	`jnl`	The MAGICAL Benchmark for Robust Imitation. CoRR Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell
2019	J	`jnl`	ASNets: Deep Learning for Generalised Planning. CoRR Sam Toyer, Felipe W. Trevizan, Sylvie Thiébaux, Lexing Xie
2019	B	`conf`	Guiding Search with Generalized Policies for Probabilistic Planning. SOCS William Shen, Felipe W. Trevizan, Sam Toyer, Sylvie Thiébaux, Lexing Xie
2019	—	`conf`	Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow. ICLR (Poster) Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
2018	A*	`conf`	Action Schema Networks: Generalised Policies With Deep Learning. AAAI Sam Toyer, Felipe W. Trevizan, Sylvie Thiébaux, Lexing Xie
2018	J	`jnl`	Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow. CoRR Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
2017	J	`jnl`	Action Schema Networks: Generalised Policies with Deep Learning. CoRR Sam Toyer, Felipe W. Trevizan, Sylvie Thiébaux, Lexing Xie
2017	Misc	`conf`	Human Pose Forecasting via Deep Markov Models. DICTA Sam Toyer, Anoop Cherian, Tengda Han, Stephen Gould
2017	J	`jnl`	Human Pose Forecasting via Deep Markov Models. CoRR Sam Toyer, Anoop Cherian, Tengda Han, Stephen Gould

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.