✨Contexts are Never Long Enough: Structured Reasoning for Scalable Question Answering over Long Document Sets
📝 Summary:
SLIDERS tackles long-document QA by extracting information into a relational database and using SQL for structured reasoning. This avoids LLM context window issues and aggregation bottlenecks, significantly outperforming traditional methods on various benchmarks.
🔹 Publication Date: Published on Apr 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.22294
• PDF: https://arxiv.org/pdf/2604.22294
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#QuestionAnswering #NLP #AI #SQL #LongDocuments
📝 Summary:
SLIDERS tackles long-document QA by extracting information into a relational database and using SQL for structured reasoning. This avoids LLM context window issues and aggregation bottlenecks, significantly outperforming traditional methods on various benchmarks.
🔹 Publication Date: Published on Apr 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.22294
• PDF: https://arxiv.org/pdf/2604.22294
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#QuestionAnswering #NLP #AI #SQL #LongDocuments