3 papers
cs.DB2024
QirK: Question Answering via Intermediate Representation on Knowledge Graphs
Jan Luca Scheerer, Anton Lykov, Moe Kayali +4
We demonstrate QirK, a system for answering natural language questions on Knowledge Graphs (KG). QirK can answer structurally complex questions that are still beyond the reach of e…
cs.DB2023
CHORUS: Foundation Models for Unified Data Discovery and Exploration
Moe Kayali, Anton Lykov, Ilias Fountalis +3
We apply foundation models to data discovery and exploration tasks. Foundation models include large language models (LLMs) that show promising performance on a range of diverse tas…
cs.AI2020
On the Tractability of SHAP Explanations
Guy Van den Broeck, Anton Lykov, Maximilian Schleich +1
SHAP explanations are a popular feature-attribution mechanism for explainable AI. They use game-theoretic notions to measure the influence of individual features on the prediction…