LC-Eval: A Bilingual Multi-Task Evaluation Benchmark for Long-Context Understanding (2025.findings-emnlp)
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Sheikh Jubair, Arwa Omayrah, Amal Alshammari, Alhanoof Althnian, Abdulhamed Alothaimen, Norah A. Alzahrani, Shahad D. Alzaidi, Nora Al-Twairesh, Abdulmohsen Al-Thubaity
| Challenge: | Recent advances in Large Language Models (LLMs) have demonstrated sophisticated capabilities, including the ability to process and comprehend extended contexts. |
| Approach: | They propose a bilingual, multi-task evaluation benchmark designed to evaluate long-context understanding in English and Arabic. |
| Outcome: | The proposed benchmark targets context lengths ranging from 4k to over 128k tokens. |
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