Rahul Seetharaman

12 papers A* 1Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ECI: Effective Contrastive Information to Evaluate Hard-Negatives. CoRR Aarush Sinha, Rahul Seetharaman, Aman Bansal
2026	A*	`conf`	From Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision-Language Models for Hateful Meme Detection. WWW Mo Wang, Kaixuan Ren, Pratik Jalan, Ahmed Ashraf, Tuong Vy Vu, Rahul Seetharaman, Shah Nawaz, Usman Naseem
2026	J	`jnl`	From Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision-Language Models for Hateful Meme Detection. CoRR Mo Wang, Kaixuan Ren, Pratik Jalan, Ahmed Ashraf, Tuong Vy Vu, Rahul Seetharaman, Shah Nawaz, Usman Naseem
2026	J	`jnl`	Scaling Laws for Reranking in Information Retrieval. CoRR Rahul Seetharaman, Aman Bansal, Hamed Zamani, Kaustubh D. Dhole
2025	—	`conf`	"Lost-In-The-Later": Framework for Quantifying Contextual Grounding in Large Language Models. ICDM (Workshops) Yufei Tao, Adam Hiatt, Rahul Seetharaman, Ameeta Agrawal
2025	J	`jnl`	"Lost-in-the-Later": Framework for Quantifying Contextual Grounding in Large Language Models. CoRR Yufei Tao, Adam Hiatt, Rahul Seetharaman, Ameeta Agrawal
2025	J	`jnl`	InsertRank: LLMs can reason over BM25 scores to Improve Listwise Reranking. CoRR Rahul Seetharaman, Kaustubh D. Dhole, Aman Bansal
2025	J	`jnl`	Leveraging Large Language Models for Predictive Analysis of Human Misery. CoRR Bishanka Seal, Rahul Seetharaman, Aman Bansal, Abhilash Nandy
2024	J	`jnl`	From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries. CoRR Hitesh Wadhwa, Rahul Seetharaman, Somyaa Aggarwal, Reshmi Ghosh, Samyadeep Basu, Soundararajan Srinivasan, Wenlong Zhao, Shreyas Chaudhari, Ehsan Aghazadeh
2024	J	`jnl`	Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis. CoRR Reshmi Ghosh, Rahul Seetharaman, Hitesh Wadhwa, Somyaa Aggarwal, Samyadeep Basu, Soundararajan Srinivasan, Wenlong Zhao, Shreyas Chaudhari, Ehsan Aghazadeh
2022	J	`jnl`	Singularity: Planet-Scale, Preemptive and Elastic Scheduling of AI Workloads. CoRR Dharma Shukla, Muthian Sivathanu, Srinidhi Viswanatha, Bhargav S. Gulavani, Rimma Nehme, Amey Agrawal, Chen Chen, Nipun Kwatra, Ramachandran Ramjee, Pankaj Sharma, Atul Katiyar, Vipul Modi, Vaibhav Sharma, Abhishek Singh, Shreshth Singhal, Kaustubh Welankar, Lu Xun, Ravi Anupindi, Karthik Elangovan, Hasibur Rahman, Zhou Lin, Rahul Seetharaman, Cheng Xu, Eddie Ailijiang, Suresh Krishnappa, Mark Russinovich
2020	—	`conf`	Stock Price Prediction using Bi-Directional LSTM based Sequence to Sequence Modeling and Multitask Learning. UEMCON Siddartha Mootha, Sashank Sridhar, Rahul Seetharaman, S. Chitrakala

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.