Papers by Gilad Fuchs
Optimizing Retrieval-Augmented Generation for E-Commerce How-To Assistance (2026.acl-industry)
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| Challenge: | Recent advances in large language models (LLMs) have significantly improved Retrieval-Augmented Generation (RAG), enabling assistants that can reliably ground responses in external knowledge sources while maintaining high-quality natural language interaction. |
| Approach: | They propose a RAG-based How-To Assistant that groundes responses in a proprietary knowledge base to provide personalized customer support. |
| Outcome: | The proposed assistant can ground responses in a proprietary knowledge base while maintaining high-quality natural language interaction. |
Is it out yet? Automatic Future Product Releases Extraction from Web Data (2022.emnlp-industry)
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| Challenge: | Identifying product releases in advance is valuable for E-Commerce marketplaces and retailers. |
| Approach: | They propose a ML-powered pipeline to automatically identify future product releases from web data. |
| Outcome: | The proposed pipeline can identify future product releases and rank their predicted demand from unstructured web pages. |