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cloud.google.com·8h ago
AI Research
arXiv CS.AI·Aug 18·5 min read
LongDocBench: Benchmarking TOC Hierarchy and Contextual Relationship Recovery in Long Documents
TL;DR
LongDocBench is a new benchmark designed to evaluate the recovery of table-of-contents hierarchies and contextual relationships in long documents. It demonstrates that incorporating these structures significantly enhances reasoning in long-document question-answering tasks.
✦ Why It Matters
Start using LongDocBench to improve your document parsing models today.
Key Takeaways
- Utilize LongDocBench for benchmarking document-level parsing tasks.
- Incorporate TOC hierarchies to enhance question-answering systems.
- Explore the dataset for training and evaluating document parsers.
- Analyze the impact of contextual relationships on reasoning tasks.
How It Works
LongDocBench provides a structured dataset with human-verified annotations that allow researchers to evaluate how well models can recover document-level structures, such as TOC hierarchies and contextual relationships. By focusing on these aspects, it enables a more comprehensive assessment of document parsing capabilities.