Rakshit S. Trivedi

32 papers A* 9A 1Journal 15Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	COLD-Steer: Steering Large Language Models via In-Context One-step Learning Dynamics. CoRR Kartik Sharma, Rakshit S. Trivedi
2026	J	`jnl`	Inner Speech as Behavior Guides: Steerable Imitation of Diverse Behaviors for Human-AI coordination. CoRR Rakshit S. Trivedi, Kartik Sharma, David C. Parkes
2025	J	`jnl`	Beyond the high score: Prosocial ability profiles of multi-agent populations. CoRR Marko Tesic, Yue Zhao, Joel Z. Leibo, Rakshit S. Trivedi, José Hernández-Orallo
2025	J	`jnl`	Efficient Knowledge Probing of Large Language Models by Adapting Pre-trained Embeddings. CoRR Kartik Sharma, Yiqiao Jin, Rakshit S. Trivedi, Srijan Kumar
2025	J	`jnl`	Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia. CoRR Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit S. Trivedi, Alexander Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P. Agapiou, Jayd Matyas, Danny Karmon, Dylan Hadfield-Menell, Natasha Jaques, Tim Baarslag, José Hernández-Orallo, Joel Z. Leibo
2025	J	`jnl`	The AI Agent Index. CoRR Stephen Casper, Luke Bailey, Rosco Hunter, Carson Ezell, Emma Cabalé, Michael Gerovitch, Stewart Slocum, Kevin Wei, Nikola Jurkovic, Ariba Khan, Phillip J. K. Christoffersen, A. Pinar Ozisik, Rakshit S. Trivedi, Dylan Hadfield-Menell, Noam Kolt
2024	A*	`conf`	Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation. ICML Kartik Sharma, Srijan Kumar, Rakshit S. Trivedi
2024	A*	`conf`	Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. NeurIPS Rakshit S. Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, Dipam Chakraborty, John P. Agapiou, Jayd Matyas, Alexander Sasha Vezhnevets, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoganaras, Yue Zhao, Marko Tesic, Natasha Jaques, Jakob N. Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Z. Leibo
2024	J	`jnl`	Normative Modules: A Generative Agent Architecture for Learning Norms that Supports Multi-Agent Cooperation. CoRR Atrisha Sarkar, Andrei Ioan Muresanu, Carter Blair, Aaryam Sharma, Rakshit S. Trivedi, Gillian K. Hadfield
2023	A*	`conf`	Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models. KDD Kartik Sharma, Rakshit S. Trivedi, Rohit Sridhar, Srijan Kumar
2022	A	`conf`	Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. AAMAS Jiachen Yang, Ethan Wang, Rakshit S. Trivedi, Tuo Zhao, Hongyuan Zha
2022	A*	`conf`	CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. ICLR Matthias Gerstgrasser, Rakshit S. Trivedi, David C. Parkes
2021	J	`jnl`	Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. CoRR Jiachen Yang, Ethan Wang, Rakshit S. Trivedi, Tuo Zhao, Hongyuan Zha
2020	A*	`conf`	GraphOpt: Learning Optimization Models of Graph Formation. ICML Rakshit S. Trivedi, Jiachen Yang, Hongyuan Zha
2020	J	`jnl`	GraphOpt: Learning Optimization Models of Graph Formation. CoRR Rakshit S. Trivedi, Jiachen Yang, Hongyuan Zha
2020	A*	`conf`	Learning Strategic Network Emergence Games. NeurIPS Rakshit S. Trivedi, Hongyuan Zha
2019	—	`conf`	DyRep: Learning Representations over Dynamic Graphs. ICLR (Poster) Rakshit S. Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha
2018	—	`conf`	Learning Deep Mean Field Games for Modeling Large Population Behavior. ICLR Jiachen Yang, Xiaojing Ye, Rakshit S. Trivedi, Huan Xu, Hongyuan Zha
2018	—	`conf`	LinkNBed: Multi-Graph Representation Learning with Entity Linkage. ACL (1) Rakshit S. Trivedi, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, Jun Ma, Hongyuan Zha
2018	J	`jnl`	LinkNBed: Multi-Graph Representation Learning with Entity Linkage. CoRR Rakshit S. Trivedi, Bunyamin Sisman, Jun Ma, Christos Faloutsos, Hongyuan Zha, Xin Luna Dong
2018	J	`jnl`	Representation Learning over Dynamic Graphs. CoRR Rakshit S. Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha
2017	J	`jnl`	Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations. CoRR Jiachen Yang, Xiaojing Ye, Rakshit S. Trivedi, Huan Xu, Hongyuan Zha
2017	A*	`conf`	Fake News Mitigation via Point Process Based Intervention. ICML Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit S. Trivedi, Elias B. Khalil, Shuang Li, Le Song, Hongyuan Zha
2017	J	`jnl`	Fake News Mitigation via Point Process Based Intervention. CoRR Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit S. Trivedi, Elias Boutros Khalil, Shuang Li, Le Song, Hongyuan Zha
2017	J	`jnl`	Know-Evolve: Deep Reasoning in Temporal Knowledge Graphs. CoRR Rakshit S. Trivedi, Hanjun Dai, Yichen Wang, Le Song
2017	A*	`conf`	Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. ICML Rakshit S. Trivedi, Hanjun Dai, Yichen Wang, Le Song
2016	—	`conf`	Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions. NIPS Yichen Wang, Nan Du, Rakshit S. Trivedi, Le Song
2016	J	`jnl`	Recurrent Coevolutionary Feature Embedding Processes for Recommendation. CoRR Hanjun Dai, Yichen Wang, Rakshit S. Trivedi, Le Song
2016	—	`conf`	Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation. DLRS@RecSys Hanjun Dai, Yichen Wang, Rakshit S. Trivedi, Le Song
2016	A*	`conf`	Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. KDD Nan Du, Hanjun Dai, Rakshit S. Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song
2013	—	`conf`	Discourse Connectors for Latent Subjectivity in Sentiment Analysis. HLT-NAACL Rakshit S. Trivedi, Jacob Eisenstein
2012	—	`conf`	CODD: constructing dataless databases. DBTest Rakshit S. Trivedi, I. Nilavalagan, Jayant R. Haritsa

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.