Irpapers – Visual embeddings vs. OCR trade-offs in scientific PDFs
Hey HN, we are releasing IRPAPERS to answer a highly pragmatic question: when building a RAG pipeline over PDFs, should you OCR the text or just embed the raw page images? Processing PDFs in production usually involves stringing together brittle OCR heuristics. While recent multimodal embeddings (like ColModernVBERT or ColPali) allow you to skip OCR entirely and retrieve directly from visual layouts, we wanted to measure if the computational overhead is actually worth the utility. The short answer: Transformer-based image pipelines won't be perfect for every use-case, but they fix exactly…
Irpapers – Visual embeddings vs. OCR trade-offs in scientific PDFs launched on February 23, 2026 with 5 votes, #1,882 of 16,627 launches that month and more than 75% of that year's launches.
What it does
Tools for various benchmarking scenarios of Weaviate's Query Agent. - weaviate/query-agent-benchmarking
A tool for benchmarking retrieval and question answering systems. Built for Weaviate's Query Agent , but designed to evaluate any system you can plug in. [9/25] 📊 Search Mode Benchmarking is live on the Weaviate Blog. git clone https://github.com/weaviate/query-agent-benchmarking.git cd query-agent-benchmarking uv sync Populate Weaviate with benchmark data: uv run python3 scripts/run-search-benchmark.py Run ask eval: uv run python3 scripts/run-ask-benchmark.py See query_agent_benchmarking/benchmark-config.yml to change the dataset, agent type ( hybrid-search , query-agent-search-mode , etc.), number of samples, and concurrency parameters. pip install query-agent-benchmarking Evaluate…from github.com
In the maker’s words, at launch
Hey HN, we are releasing IRPAPERS to answer a highly pragmatic question: when building a RAG pipeline over PDFs, should you OCR the text or just embed the raw page images? Processing PDFs in production usually involves stringing together brittle OCR heuristics. While recent multimodal embeddings (like ColModernVBERT…
Does a similar job
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Open-source Rule-based PDF parser for RAG2024 · github.com · ▲293The PDF parser is a rule based parser which uses text co-ordinates (boundary box), graphics and font data. The PDF parser works off text layer and also offers a OCR option to automatically use OCR if there are scanned pages in your PDFs. The OCR feature is based off a modified version of tika which uses tesseract underneath. The PDF Parser offers the following features: * Sections and subsections along with their levels. * Paragraphs - combines lines. * Links between sections and paragraphs. * Tables along with the section the tables are found in. * Lists and nested lists. * Join content…
Zerox – Document OCR with GPT-mini2024 · github.com · ▲246This started out as a weekend hack with gpt-4-mini, using the very basic strategy of "just ask the ai to ocr the document". But this turned out to be better performing than our current implementation of Unstructured/Textract. At pretty much the same cost. I've tested almost every variant of document OCR over the past year, especially trying things like table / chart extraction. I've found the rules based extraction has always been lacking. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. Using a vision model just make sense! In…
I built a free alternative to Adobe Acrobat PDF viewer2025 · github.com · ▲357I built EmbedPDF: an MIT-licensed, open-source PDF viewer that aims to match all of Adobe Acrobat’s paid features… for free. Already working: - Annotations (highlight, sticky notes, free text, ink) - True redaction (content actually removed) - Search, text selection, zoom, rotation - Runs fully in the browser, no server needed - Drop-in SDK for React, Vue, Preact, vanilla JS Why? Acrobat is heavy, closed, and pricey. I wanted something lightweight, hackable, and embeddable anywhere. Demo: https://app.embedpdf.com/ Website: https://www.embedpdf.com/ GitHub:…
OCR pipeline for ML training (tables, diagrams, math, multilingual)2025 · github.com · ▲170Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…
Morphik – Open-source RAG that understands PDF images, runs locally2025 · github.com · ▲200Hey HN, we’re Adi and Arnav. A few months ago, we hit a wall trying to get LLMs to answer questions over research papers and instruction manuals. Everything worked fine, until the answer lived inside an image or diagram embedded in the PDF. Even GPT‑4o flubbed it (we recently tried O3 with the same, and surprisingly it flubbed it too). Naive RAG pipelines just pulled in some text chunks and ignored the rest. We took an invention disclosure PDF (https://drive.google.com/file/d/1ySzQgbNZkC5dPLtE3pnnVL2rW_9...) containing an IRR‑vs‑frequency graph and asked GPT “From…
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