Most people already know the basic checks before opening a file. They also apply to PDFs: verifying the sender looks legitimate, exercising caution before opening or downloading unexpected attachments ...
Newsrooms have long used AI to sift through document dumps. Now that same tech is being used to build search tools for ...
To protect private information stored in text embeddings, it’s essential to de-identify the text before embedding and storing it in a vector database. In this article, we'll demonstrate how to ...
Reproducible, parser-agnostic benchmarks for turning PDFs into Markdown—and measuring downstream usefulness with retrieval-QA, not just visual fidelity. We use two human-in-the-loop methods plus one ...
A focused pipeline to parse medical guidelines (PDF/HTML) into structured JSON for downstream clinical RAG or summarization. This implements models, parsers, normalization utils, and a CLI to ingest ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results