Papers by Mehran Haddadi

1 papers
Comparing Text Compression Capabilities of Large Language Models with Traditional Compression Algorithms (2026.eacl-srw)

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Challenge: Experimental results show that large language models outperform baselines on non-English datasets . traditional methods remained dataset-agnostic, and the results suggest that current methods are impractical for the compression task.
Approach: They evaluate the non-English and unstructured text compression performance of Large Language Models . they compare them with traditional baselines on datasets from eight most widely spoken languages .
Outcome: The evaluated LLM outperformed baselines on non-English datasets . the results show that the current methods are highly impractical for the compression task .

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