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Prompting as Probing: Using Language Models for Knowledge Base Construction.

, , , , , и . LM-KBC@ISWC, том 3274 из CEUR Workshop Proceedings, стр. 11-34. CEUR-WS.org, (2022)

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Emile Schyns

Emile Paes

Emile Nosseir

Emile Cherbuliez

Emile Krier

 

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A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference., , , , и . CoRR, (2022)Prompting as Probing: Using Language Models for Knowledge Base Construction., , , , , и . LM-KBC@ISWC, том 3274 из CEUR Workshop Proceedings, стр. 11-34. CEUR-WS.org, (2022)Analysis of Measure-Valued Derivatives in a Reinforcement Learning Actor-Critic Framework., , и . WSC, стр. 2736-2747. IEEE, (2022)Optimisation in Neurosymbolic Learning Systems.. CoRR, (2024)Refining neural network predictions using background knowledge., , , и . Mach. Learn., 112 (9): 3293-3331 (сентября 2023)Analyzing Differentiable Fuzzy Logic Operators., , и . Artif. Intell., (2022)Semi-Supervised Learning using Differentiable Reasoning., , и . CoRR, (2019)Benefits of Social Learning in Physical Robots., , , , , , , и . SSCI, стр. 851-858. IEEE, (2018)Analyzing Differentiable Fuzzy Logic Operators., , и . CoRR, (2020)IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation., , , и . CoRR, (2023)