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cs.CL2023
Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
Pengcheng Jiang, Shivam Agarwal, Bowen Jin +3
The mission of open knowledge graph (KG) completion is to draw new findings from known facts. Existing works that augment KG completion require either (1) factual triples to enlarg…
cs.CL2023★ 35 cited
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Large language models (LLMs) specializing in natural language generation (NLG) have recently started exhibiting promising capabilities across a variety of domains. However, gauging…