SPECTER is a pre-trained language model to generate document-level embedding of documents. It is pre-trained on a a powerful signal of document-level relatedness: the citation graph. Unlike existing pretrained language models, SPECTER can be easily applied to downstream applications without task-specific fine-tuning.

Paper: SPECTER: Document-level Representation Learning using Citation-informed Transformers

Original Repo: Github

Evaluation Benchmark: SciDocs

Authors: Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, Daniel S. Weld

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