Paper proposes knowledge-weighted fine-tuning to train language models to better recognize knowledge limits and say "I don't know" instead of hallucinating. Addresses the critical problem of model calibration and epistemic uncertainty in LLM deployment.
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What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say "I Don't Know"
Knowledge-weighted fine-tuning trains language models to recognize epistemic boundaries and say "I don't know" instead of hallucinating, directly improving model calibration and deployment reliability.
Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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