Papers by Suleiman A. Khan

2 papers
Leveraging Product Catalog Patterns for Multilingual E-commerce Product Attribute Prediction (2025.emnlp-industry)

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Challenge: E-commerce stores increasingly use Large Language Models to improve catalog data quality . a critical challenge is accurately predicting missing structured attribute values .
Approach: They propose a retrieval-augmented system that leverages existing product catalog entries to guide LLM predictions for missing attributes.
Outcome: The proposed system improves catalog data quality by 34% and accuracy by 0.8% . the proposed model can predict missing attributes in multilingual product catalogs .
Auto prompting without training labels: An LLM cascade for product quality assessment in e-commerce catalogs (2025.emnlp-industry)

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Challenge: Our system generates and refines prompts for evaluating attribute quality across tens of thousands of product category–attribute pairs.
Approach: They propose a free cascade for auto-prompting Large Language Models (LLMs) that generates and refines prompts for evaluating attribute quality across tens of thousands of product category–attribute pairs.
Outcome: The proposed system improves precision and recall by 8–10% over chain-of-thought prompting while reducing domain expert effort from 5.1 hours to 3 minutes per attribute.

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