1 citations · 1 across the 2 of their papers we have counts for
6 papers
Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents
Maria Leonor Pacheco, Max von Hippel, Ben Weintraub +2
Automated attack discovery techniques, such as attacker synthesis or model-based fuzzing, provide powerful ways to ensure network protocols operate correctly and securely. Such tec…
Identifying Morality Frames in Political Tweets using Relational Learning
Shamik Roy, Maria Leonor Pacheco, Dan Goldwasser
Extracting moral sentiment from text is a vital component in understanding public opinion, social movements, and policy decisions. The Moral Foundation Theory identifies five moral…
Modeling Human Mental States with an Entity-based Narrative Graph
I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser
Understanding narrative text requires capturing characters' motivations, goals, and mental states. This paper proposes an Entity-based Narrative Graph (ENG) to model the internal-s…
Randomized Deep Structured Prediction for Discourse-Level Processing
Manuel Widmoser, Maria Leonor Pacheco, Jean Honorio +1
Expressive text encoders such as RNNs and Transformer Networks have been at the center of NLP models in recent work. Most of the effort has focused on sentence-level tasks, capturi…
Modeling Content and Context with Deep Relational Learning
Maria Leonor Pacheco, Dan Goldwasser
Building models for realistic natural language tasks requires dealing with long texts and accounting for complicated structural dependencies. Neural-symbolic representations have e…
Leveraging Textual Specifications for Grammar-based Fuzzing of Network Protocols
Samuel Jero, Maria Leonor Pacheco, Dan Goldwasser +1
Grammar-based fuzzing is a technique used to find software vulnerabilities by injecting well-formed inputs generated following rules that encode application semantics. Most grammar…