title: PhysBERT: A Text Embedding Model for Physics Scientific Literature
summary: The specialized language and complex concepts in physics pose significant
  challenges for information extraction through Natural Language Processing
  (NLP). Central to effective NLP applications is the text embedding model, which
  converts text into dense vector representations for efficient information
  retrieval and semantic analysis. In this work, we introduce PhysBERT, the first
  physics-specific text embedding model. Pre-trained on a curated corpus of 1.2
  million arXiv physics papers and fine-tuned with supervised data, PhysBERT
  outperforms leading general-purpose models on physics-specific tasks including
  the effectiveness in fine-tuning for specific physics subdomains.
paper_authors._id: 66c5a926e8f01fe34ec01d7d
paper_authors.name: Thorsten Hellert
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2024-08-21T08:45:27.429Z
paper_authors._id: 6575167c983403462a417aa2
paper_authors.avatarUrl: /avatars/da05451d86e469fe87aee328103a5fd7.svg
paper_authors.fullname: Thorsten  Hellert
paper_authors.type: user
paper_authors.user: thellert
paper_authors._id: 66c5a926e8f01fe34ec01d7e
paper_authors.name: João Montenegro
paper_authors._id: 66c5a926e8f01fe34ec01d7f
paper_authors.name: Andrea Pollastro
paper_title: PhysBERT: A Text Embedding Model for Physics Scientific Literature
paper_summary: The specialized language and complex concepts in physics pose significant
  challenges for information extraction through Natural Language Processing
  (NLP). Central to effective NLP applications is the text embedding model, which
  converts text into dense vector representations for efficient information
  retrieval and semantic analysis. In this work, we introduce PhysBERT, the first
  physics-specific text embedding model. Pre-trained on a curated corpus of 1.2
  million arXiv physics papers and fine-tuned with supervised data, PhysBERT
  outperforms leading general-purpose models on physics-specific tasks including
  the effectiveness in fine-tuning for specific physics subdomains.
paper_ai_summary: PhysBERT is a physics-specific text embedding model pre-trained on arXiv physics papers, surpassing general-purpose models in physics-related tasks and fine-tuning for subdomains.
paper_ai_keywords: text embedding model NLP PhysBERT arXiv physics papers fine-tuning physics-specific tasks