activity
20132026
most citedInforming clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes

27 citations · 95 across the 53 of their papers we have counts for

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Showing 2026Show all

17 papers · 1 filter

cs.LG2026

Adaptive Ensemble Selection for Noisy Labels on Tabular Data

Faizaan Ali, Inwon Kang, Oshani Seneviratne

Incorrect or corrupted labels in tabular datasets can significantly degrade supervised learning performance, particularly when mislabeling is subtle and not easily detectable from…

cs.AI2026

Cost Characterization of Vertically Partitioned Federated Knowledge Graphs

Md Saikat Islam Khan Bappy, Oshani Seneviratne

Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming a vertical partition. Answer…

cs.AI2026

FedV-KGQA in Practice: Design Lessons and an Interactive Prototype

Md Saikat Islam Khan Bappy, Oshani Seneviratne

Knowledge graph question answering usually assumes that one system can reach the whole graph. In practice, facts are often held by organizations that share entity identifiers but o…

cs.LG2026

When Connected Does Not Mean Similar: Charting the Homophily Boundary of SNAP-KG for Streaming Entity Integration

Jui-Chien Lin, Oshani Seneviratne

SNAP-KG is a framework for assigning newly arriving entities to semantic communities in a growing knowledge graph (KG) using only their raw features, with no graph access and no re…

cs.LG2026

SNAP-KG: Streaming Node Assignment via Projection for Knowledge Graph Entity Integration

Jui-Chien Lin, Mohammad Mohammadi Amiri, Oshani Seneviratne

Knowledge graph (KG) construction pipelines must continuously integrate newly arriving entities into a growing graph. Unlike inserting triples between existing nodes, a newly arriv…

cs.AI2026

FedV-KGQA: Multi-Hop Question Answering over Vertically Partitioned Knowledge Graphs

Md Saikat Islam Khan Bappy, Oshani Seneviratne

Real-world data for knowledge graph question answering is often distributed across different organizations due to governance and data sovereignty constraints. While centralized sys…

cs.IR2026

GrOIL: Graph-Grounded Domain Ontology Induction with Constrained LLM Mediation

Maruf Ahmed Mridul, Abid Talukder, Oshani Seneviratne

Constructing formal ontologies from domain documents requires simultaneously enforcing corpus grounding, vocabulary consistency, axiom-level expressivity, and end-to-end provenance…

cs.IR2026

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…

cs.LG2026

SemStruct: Contextualizing Semantic Embeddings with Structural Information for Schema Matching

Inwon Kang, Kavitha Srinivas, Nandana Mihindukulasooriya +4

Schema matching is a fundamental step in integrating heterogeneous data sources. While Pre-trained Language Models (PLMs) have revolutionized this task by capturing linguistic sema…

cs.AI2026

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

Abid Talukder, Maruf Ahmed Mridul, Oshani Seneviratne

Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise,…

cs.LG2026

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.…

cs.AI2026

A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness

Maruf Ahmed Mridul, Rohit Kapa, Oshani Seneviratne

Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions that users actually care abo…

cs.OH2026

Personal Health Data Integration and Intelligence through Semantic Web and Blockchain Technologies

Oshani Seneviratne, Manan Shukla, Jianjing Lin

Data integration among various stakeholders in the healthcare space remains a challenge, despite the impressive advances in Health AI in the past decade. There is a lot of ``messy'…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

Measuring Privacy Risks and Tradeoffs in Financial Synthetic Data Generation

Michael Zuo, Inwon Kang, Stacy Patterson +1

We explore the privacy-utility tradeoff of synthetic data generation schemes on tabular financial datasets, a domain characterized by high regulatory risk and severe class imbalanc…

cs.CL2026★ 1 cited

Language Model Representations for Efficient Few-Shot Tabular Classification

Inwon Kang, Parikshit Ram, Yi Zhou +2

The Web is a rich source of structured data in the form of tables, from product catalogs and knowledge bases to scientific datasets. However, the heterogeneity of the structure and…