Papers by Khaloud Suliman Alkhalefah
Halwasa: Quantify and Analyze Hallucinations in Large Language Models: Arabic as a Case Study (2024.lrec-main)
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| Challenge: | Large Language Models (LLMs) generate text that is factually incorrect, nonsensical, or misleading. |
| Approach: | They create a large Arabic dataset that contains 10K of LLM generated sentences and annotate it for factuality and correctness. |
| Outcome: | The proposed dataset analyzes 10K of generated sentences and finds 25% of them are factually incorrect. |