Tapas Nayak - RankMe

34 papers A* 1A 1B 4Misc 2Journal 18Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Are Relational Triple Extraction Frameworks Sufficient for Hyper-relational Facts ? IJCNLP-AACL (Short Papers) Pratik Saini, Chayan Sarkar, Tapas Nayak
2025	—	`conf`	Effective Modeling of Generative Framework for Document-level Relational Triple Extraction. COLING Workshops Pratik Saini, Tapas Nayak
2024	J	`jnl`	MatSciRE: Leveraging Pointer Networks to Automate Entity and Relation Extraction for Material Science Knowledge-base Construction. CoRR Ankan Mullick, Akash Ghosh, G. Sai Chaitanya, Samir Ghui, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, Pawan Goyal
2023	J	`jnl`	A Two-step Approach for Handling Zero-Cardinality in Relation Extraction. CoRR Pratik Saini, Tapas Nayak, Samiran Pal, Indrajit Bhattacharya
2023	J	`jnl`	Adapting Pre-trained Generative Models for Extractive Question Answering. CoRR Prabir Mallick, Tapas Nayak, Indrajit Bhattacharya
2023	—	`conf`	Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks? IJCNLP (2) Pratik Saini, Tapas Nayak, Indrajit Bhattacharya
2023	J	`jnl`	Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks? CoRR Pratik Saini, Tapas Nayak, Indrajit Bhattacharya
2023	J	`jnl`	FinRED: A Dataset for Relation Extraction in Financial Domain. CoRR Soumya Sharma, Tapas Nayak, Arusarka Bose, Ajay Kumar Meena, Koustuv Dasgupta, Niloy Ganguly, Pawan Goyal
2023	—	`conf`	tagE: Enabling an Embodied Agent to Understand Human Instructions. EMNLP (Findings) Chayan Sarkar, Avik Mitra, Pradip Pramanick, Tapas Nayak
2023	J	`jnl`	tagE: Enabling an Embodied Agent to Understand Human Instructions. CoRR Chayan Sarkar, Avik Mitra, Pradip Pramanick, Tapas Nayak
2022	—	`conf`	A Generative Approach for Financial Causality Extraction. WWW (Companion Volume) Tapas Nayak, Soumya Sharma, Yash Butala, Koustuv Dasgupta, Pawan Goyal, Niloy Ganguly
2022	J	`jnl`	A Generative Approach for Financial Causality Extraction. CoRR Tapas Nayak, Soumya Sharma, Yash Butala, Koustuv Dasgupta, Pawan Goyal, Niloy Ganguly
2022	B	`conf`	A Weak Supervision Approach for Predicting Difficulty of Technical Interview Questions. COLING Arpita Kundu, Subhasish Ghosh, Pratik Saini, Tapas Nayak, Indrajit Bhattacharya
2022	J	`jnl`	Exploring Generative Models for Joint Attribute Value Extraction from Product Titles. CoRR Kalyani Roy, Tapas Nayak, Pawan Goyal
2022	—	`conf`	FinRED: A Dataset for Relation Extraction in Financial Domain. WWW (Companion Volume) Soumya Sharma, Tapas Nayak, Arusarka Bose, Ajay Kumar Meena, Koustuv Dasgupta, Niloy Ganguly, Pawan Goyal
2022	B	`conf`	Using Sentence-level Classification Helps Entity Extraction from Material Science Literature. LREC Ankan Mullick, Shubhraneel Pal, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, Pawan Goyal
2021	Misc	`conf`	A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents. RANLP Tapas Nayak, Hwee Tou Ng
2021	J	`jnl`	A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents. CoRR Tapas Nayak, Hwee Tou Ng
2021	A	`conf`	Aspect Sentiment Triplet Extraction Using Reinforcement Learning. CIKM Samson Yu Bai Jian, Tapas Nayak, Navonil Majumder, Soujanya Poria
2021	J	`jnl`	Aspect Sentiment Triplet Extraction Using Reinforcement Learning. CoRR Samson Yu Bai Jian, Tapas Nayak, Navonil Majumder, Soujanya Poria
2021	J	`jnl`	Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey. CoRR Tapas Nayak, Navonil Majumder, Pawan Goyal, Soujanya Poria
2021	J	`jnl`	Deep Neural Approaches to Relation Triplets Extraction: a Comprehensive Survey. Cogn. Comput. Tapas Nayak, Navonil Majumder, Pawan Goyal, Soujanya Poria
2021	J	`jnl`	Deep Neural Networks for Relation Extraction. CoRR Tapas Nayak
2021	Misc	`conf`	Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise Filtering. RANLP Tapas Nayak, Navonil Majumder, Soujanya Poria
2021	J	`jnl`	Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise Filtering. CoRR Tapas Nayak, Navonil Majumder, Soujanya Poria
2021	—	`conf`	PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction. EMNLP (1) Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya, Pawan Goyal
2021	J	`jnl`	PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction. CoRR Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya, Pawan Goyal
2021	J	`jnl`	RTE: A Tool for Annotating Relation Triplets from Text. CoRR Ankan Mullick, Animesh Bera, Tapas Nayak
2020	A*	`conf`	Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction. AAAI Tapas Nayak, Hwee Tou Ng
2019	B	`conf`	Effective Attention Modeling for Neural Relation Extraction. CoNLL Tapas Nayak, Hwee Tou Ng
2019	J	`jnl`	Effective Attention Modeling for Neural Relation Extraction. CoRR Tapas Nayak, Hwee Tou Ng
2019	J	`jnl`	Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction. CoRR Tapas Nayak, Hwee Tou Ng
2016	—	`conf`	CATaLog Online: A Web-based CAT Tool for Distributed Translation with Data Capture for APE and Translation Process Research. COLING (Demos) Santanu Pal, Sudip Kumar Naskar, Marcos Zampieri, Tapas Nayak, Josef van Genabith
2016	B	`conf`	CATaLog Online: Porting a Post-editing Tool to the Web. LREC Santanu Pal, Marcos Zampieri, Sudip Kumar Naskar, Tapas Nayak, Mihaela Vela, Josef van Genabith

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.