TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction (2024.naacl-long)
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| Challenge: | Large language models (LLMs) often generate incorrect responses based on made-up facts, which are called hallucinations. |
| Approach: | They propose a framework that combines Retrieval Augmented Generation with conformal prediction to provide the first end-to-end statistical correctness guarantee for RAG. |
| Outcome: | The proposed framework reduces prediction set size by 16.2% on average compared to an ablation. |
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