LongHisDoc: A Comprehensive Benchmark for Chinese Long Historical Document Understanding
To bridge this gap, we introduce LongHisDoc, the first benchmark tailored for long historical document understanding.
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Key points
- Chinese historical documents are invaluable cultural treasures, but their complexity poses significant comprehension challenges for non-specialists.
- Despite the success of Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) in modern document tasks, their capabilities in Long (full-book) Historical Document understanding remain largely unexplored.
- LongHisDoc comprises 1,012 expert-annotated QA pairs derived from 101 PDF documents, with an average of 85.1 pages and 42,776.4 tokens per document.
- Furthermore, we assess various modal retrievers and the end-to-end RAG performance to provide references for Retrieval-Augmented Generation (RAG) systems.
Sources (1)
- [1]LongHisDoc: A Comprehensive Benchmark for Chinese Long Historical Document UnderstandingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 10, 03:44 AM
To bridge this gap, we introduce LongHisDoc, the first benchmark tailored for long historical document understanding.
Chinese historical documents are invaluable cultural treasures, but their complexity poses significant comprehension challenges for non-specialists.
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