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Summary Workbench

Unifying the application and evaluation of text summarization models. [Paper] [Documentation] [Live Demo]

Accepted at EMNLP 2022 (Demo track). 🎉 🎉

📢 Updates (3-12-2022)

  1. Integrated 2 new models and their variants (6 in total): BRIO trained on news, Schnitsum trained on scholary documents.
  2. Integrated contrastive search for more fluent summaries. User can now toggle between regular and contrasitve search for supported models.
  3. Improvements to the UI responsiveness on smaller devices.

Summarize

Create a Request

Create a Request

Inspect the Results

Inspect the Results

Evaluate

Create a Request

Create a Request

Inspect the Results

Scores

Scores

Visualize Text Examples

Visualize Text Examples

Plot Scores against each other

Plot Scores against each other

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Framework for evaluation of RAG text re-use.

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  • JavaScript 55.7%
  • Python 42.5%
  • Other 1.8%