Papers by Fatemeh Taheri Dezaki

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Challenge:	Large language models excel at structured information generation but face cost and latency challenges when deployed at scale in user-facing products.
Approach:	They propose a parameter efficient supervised fine-tuning pipeline for adapting a small language model to structured attribute generation in e-commerce product listing.
Outcome:	The proposed model reduces inference costs by 98% and latency by 70% on a large-scale product listing service while preserving an 86.4% user acceptance rate.