Abstract: Document content extraction is a critical task in computer vision, underpinning the data needs of large language models (LLMs) and retrieval-augmented generation (RAG) systems. Despite ...

In the current landscape of Retrieval-Augmented Generation (RAG), the primary bottleneck for developers is no longer the large language model (LLM) itself, but the data ingestion pipeline. For ...

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A security vulnerability has been disclosed in the popular binary-parser npm library that, if successfully exploited, could result in the execution of arbitrary JavaScript. The vulnerability, tracked ...

A robust, intelligent Python tool for extracting line items and totals from vendor PDF invoices. Handles various invoice layouts with smart pattern recognition and supports both digital and scanned ...

A security flaw in the widely-used Apache Tika XML document extraction utility, originally made public last summer, is wider in scope and more serious than first thought, the project’s maintainers ...

The bug allows attackers to carry out XML External Entity (XXE) injection attacks via crafted XFA files inside PDF files. A critical-severity vulnerability in the Apache Tika open source analysis ...

There is a lot of enterprise data trapped in PDF documents. To be sure, gen AI tools have been able to ingest and analyze PDFs, but accuracy, time and cost have been less than ideal. New technology ...

Cybersecurity researchers have disclosed details of a high-severity flaw impacting the popular async-tar Rust library and its forks, including tokio-tar, that could result in remote code execution ...

Automated Resume Parser – Built at Codec Technologies during internship. Designed an intelligent parser that extracts candidate details (name, contact, skills, experience, education) from PDF/DOCX ...