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[Paper Club] DocETL: Agentic Query Rewriting + Eval for Complex Document Processing w Shreya Shankar

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youtube.com
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Latent Space
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DocETL, a research system for running language-model operations over large collections of documents, treats a difficult document-processing request as a workflow that can be reorganized. In the paper discussion, its author explains that asking a model to extract many fields from a long document in one operation may fail because the request is too demanding.

A rewrite changes the processing pipeline: it can split the material, perform narrower extraction steps and combine their results. The document itself is not what gets rewritten. This gives developers a structured way to change how an extraction task is carried out, rather than relying entirely on revisions to one large prompt.

Terms in this piece · Glossary
  • LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
  • eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
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