9 papers
From "Strings" to "Things" for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems
Abhirup Dasgupta, Fernando Spadea, Oshani Seneviratne
Personal Knowledge Graphs (PKGs) offer a privacy-preserving framework for modeling user preferences, yet constructing them from unstructured, decentralized conversational data rema…
From Risk to Rescue: An Agentic Survival Analysis Framework for Liquidation Prevention
Fernando Spadea, Oshani Seneviratne
Decentralized Finance (DeFi) lending protocols like Aave v3 rely on over-collateralization to secure loans, yet users frequently face liquidation due to volatile market conditions.…
Benchmarking Temporal Web3 Intelligence: Lessons from the FinSurvival 2025 Challenge
Oshani Seneviratne, Fernando Spadea, Adrien Pavao +2
Temporal Web analytics increasingly relies on large-scale, longitudinal data to understand how users, content, and systems evolve over time. A rapidly growing frontier is the \emph…
Federated Personal Knowledge Graph Completion with Lightweight Large Language Models for Personalized Recommendations
Fernando Spadea, Oshani Seneviratne
Personalized recommendation increasingly relies on private user data, motivating approaches that can adapt to individuals without centralizing their information. We present Federat…
Explainable Federated Learning for U.S. State-Level Financial Distress Modeling
Lorenzo Carta, Fernando Spadea, Oshani Seneviratne
We present the first application of federated learning (FL) to the U.S. National Financial Capability Study, introducing an interpretable framework for predicting consumer financia…
Aligning Language Models with Investor and Market Behavior for Financial Recommendations
Fernando Spadea, Oshani Seneviratne
Most financial recommendation systems often fail to account for key behavioral and regulatory factors, leading to advice that is misaligned with user preferences, difficult to inte…