Papers by Tajana Rosing

1 papers
TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs (2025.acl-long)

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Challenge: specialized language models do not show simultaneous memory saving and inference speedup at deployment time.
Approach: They develop a layer-wise specialization technique that reduces the depth of LLMs by progressive layer dropping and compares it to other algorithms for inference.
Outcome: The proposed model retains LLMs’ capacity in specific domains and achieves inference speedup irrespective of hardware and deep learning frameworks.

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