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: Remaining "grounded" to the document rather than relying on internal (and potentially outdated) training data. 4. Conclusion

: Ensuring answers are grounded strictly in the provided text without "hallucinations". ntq.rar

: Combining multiple, non-contiguous parts of a document into a single fluid response. : Remaining "grounded" to the document rather than

: Identifying when a provided document does not contain the answer is a critical real-world skill that models still struggle with. : Combining multiple, non-contiguous parts of a document

: Distilling large passages into grounded answers that are often three times smaller than the source. 3. Key Challenges in Long-form QA (LFQA)

According to researchers from the ACL Anthology , LLMs still face significant hurdles in these areas:

Benchmarking the Future: The Evolution of Natural Questions (NQ) and RAG Systems 1. Introduction to Natural Questions (NQ)