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20232025
most citedExploring In-Context Learning Capabilities of Foundation Models for Generating Knowledge Graphs from Text

8 citations · 13 across the 5 of their papers we have counts for

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5 papers

quant-ph2025

QCardEst/QCardCorr: Quantum Cardinality Estimation and Correction

Tobias Winker, Jinghua Groppe, Sven Groppe

Cardinality estimation is an important part of query optimization in DBMS. We develop a Quantum Cardinality Estimation (QCardEst) approach using Quantum Machine Learning with a Hyb…

quant-ph20242 cited

QCE'24 Tutorial: Quantum Annealing -- Emerging Exploration for Database Optimization

Nitin Nayak, Manuel Schönberger, Valter Uotila +4

Quantum annealing is a meta-heuristic approach tailored to solve combinatorial optimization problems with quantum annealers. In this tutorial, we provide a fundamental and comprehe…

cs.SE20243 cited

Variables are a Curse in Software Vulnerability Prediction

Jinghua Groppe, Sven Groppe, Ralf Möller

Deep learning-based approaches for software vulnerability prediction currently mainly rely on the original text of software code as the feature of nodes in the graph of code and th…

cs.CL2024

Are Large Language Models the New Interface for Data Pipelines?

Sylvio Barbon Junior, Paolo Ceravolo, Sven Groppe +5

A Language Model is a term that encompasses various types of models designed to understand and generate human communication. Large Language Models (LLMs) have gained significant at…

cs.CL20238 cited

Exploring In-Context Learning Capabilities of Foundation Models for Generating Knowledge Graphs from Text

Hanieh Khorashadizadeh, Nandana Mihindukulasooriya, Sanju Tiwari +2

Knowledge graphs can represent information about the real-world using entities and their relations in a structured and semantically rich manner and they enable a variety of downstr…