Leilani H. Gilpin

25 papers A* 2A 1B 2C 1Misc 1Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Follow My Lead: Logical Fallacy Classification with Knowledge-Augmented LLMs. CoRR Olivia Peiyu Wang, Tashvi Bansal, Ryan Bai, Emily M. Chui, Leilani H. Gilpin
2025	J	`jnl`	Guaranteed Optimal Compositional Explanations for Neurons. CoRR Biagio La Rosa, Leilani H. Gilpin
2025	J	`jnl`	Open Vocabulary Compositional Explanations for Neuron Alignment. CoRR Biagio La Rosa, Leilani H. Gilpin
2025	C	`ed.`	Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning (NeSy 2025), 8-10 September 2025, Santa Cruz, CA, USA NeSy Leilani H. Gilpin, Eleonora Giunchiglia, Pascal Hitzler, Emile van Krieken
2025	J	`jnl`	VFSI: Validity First Spatial Intelligence for Constraint-Guided Traffic Diffusion. CoRR Kargi Chauhan, Leilani H. Gilpin
2024	—	`conf`	ProSLM: A Prolog Synergized Language Model for explainable Domain Specific Knowledge Based Question Answering. NeSy (2) Priyesh Vakharia, Abigail Kufeldt, Max Meyers, Ian Lane, Leilani H. Gilpin
2024	J	`jnl`	Right this way: Can VLMs Guide Us to See More to Answer Questions? CoRR Li Liu, Diji Yang, Sijia Zhong, Kalyana Suma Sree Tholeti, Lei Ding, Yi Zhang, Leilani H. Gilpin
2024	J	`jnl`	Slug Mobile: Test-Bench for RL Testing. CoRR Jonathan Wellington Morris, Vishrut Shah, Alex Besanceney, Daksh Shah, Leilani H. Gilpin
2023	A*	`conf`	Accountability Layers: Explaining Complex System Failures by Parts. AAAI Leilani H. Gilpin
2023	J	`jnl`	Anticipatory Thinking Challenges in Open Worlds: Risk Management. CoRR Adam Amos-Binks, Dustin Dannenhauer, Leilani H. Gilpin
2023	J	`jnl`	Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations. CoRR Shiyuan Huang, Siddarth Mamidanna, Shreedhar Jangam, Yilun Zhou, Leilani H. Gilpin
2023	J	`jnl`	Convolutional Neural Network Model for Diabetic Retinopathy Feature Extraction and Classification. CoRR Sharan Subramanian, Leilani H. Gilpin
2023	J	`jnl`	The anticipatory paradigm. AI Mag. Adam Amos-Binks, Dustin Dannenhauer, Leilani H. Gilpin
2023	J	`jnl`	Towards a fuller understanding of neurons with Clustered Compositional Explanations. CoRR Biagio La Rosa, Leilani H. Gilpin, Roberto Capobianco
2022	J	`jnl`	"Explanation" is Not a Technical Term: The Problem of Ambiguity in XAI. CoRR Leilani H. Gilpin, Andrew R. Paley, Mohammed A. Alam, Sarah Spurlock, Kristian J. Hammond
2021	Misc	`conf`	Anticipatory Thinking: A Testing and Representation Challenge for Self-Driving Cars. CISS Leilani H. Gilpin
2021	B	`conf`	Explaining Multimodal Errors in Autonomous Vehicles. DSAA Leilani H. Gilpin, Vishnu Penubarthi, Lalana Kagal
2019	A	`conf`	An Adaptable Self-Monitoring Framework for Opaque Machines. AAMAS Leilani H. Gilpin, Lalana Kagal
2019	J	`jnl`	Explaining Explanations to Society. CoRR Leilani H. Gilpin, Cecilia Testart, Nathaniel Fruchter, Julius Adebayo
2019	J	`jnl`	Reports of the AAAI 2019 Spring Symposium Series. AI Mag. Ioana Baldini, Clark W. Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson
2018	J	`jnl`	Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning. CoRR Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal
2018	B	`conf`	Explaining Explanations: An Overview of Interpretability of Machine Learning. DSAA Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal
2018	—	`conf`	Perception of Speaker Personality Traits Using Speech Signals. CHI Extended Abstracts Leilani H. Gilpin, Danielle M. Olson, Tarfah Alrashed
2018	—	`conf`	Reasonable Perception: Connecting Vision and Language Systems for Validating Scene Descriptions. HRI (Companion) Leilani H. Gilpin, Cagri Zaman, Danielle Olson, Ben Z. Yuan
2018	A*	`conf`	Reasonableness Monitors. AAAI Leilani H. Gilpin

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.