Author

Brayan Impata

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Jul 2026

SynthAVE: Scalable Synthetic Labeling for E-Commerce with LLM-Arena Validation

SynthAVE is presented, a large-scale benchmark for attribute-value verification spanning 12,726 products across 229 product types, 792 attributes, and 4 languages and demonstrates that diverse models with varying individual judgments aggregate into highly reliable predictions, enabling cost-effective validation at scal...

Andrea Scarinci, V. Negri, Brayan Impata et al. · arXiv.org · 0 citations

Scalable Visual Attribute Recognition in E-Commerce Products via Automated Synthetic Label Generation

This work introduces a scalable approach that uses CLIP models to automatically generate synthetic labeled datasets, significantly reducing the need for manual annotation and demonstrates that synthetic labeling with vision-language models could serve as a practical and effective approach for large-scale visual attribu...

V. Martinez, V. Negri, Brayan Impata et al. · 0 citations

#artificial intelligence Review Jul 2026

SynthAVE: Scalable Synthetic Labeling for E-Commerce with LLM-Arena Validation

Fine-tuning large language models (LLMs) for e-commerce attribute extraction requires labeled data representative across thousands of product types, attributes, and multiple languages. This combinatorial scale translates to millions of annotations, rendering human labeling prohibitively costly. While recent work has de...

Andrea Scarinci, V. Negri, Brayan Impata et al. · 0 citations