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cs.LG2026
LLMs as Feature Engineers for Text-and-Tabular Prediction
Merwan Barlier, Blaz Skrlj
We introduce an iterative framework that automates the extraction of interpretable, schema-bound categorical features from unstructured text for tabular prediction models. To navig…
cs.LG2026
Building a User Foundation Model for the Open Web
Solal Vernier, Ivan Can Arisoy, Merwan Barlier +1
User foundation models have demonstrated strong results in e-commerce and social recommendation, but most industrial deployments assume environments where user identity is stable a…
cs.AI2026
PromptPack: Scaling LLM Annotation Agents for Online Recommendation
Sebastian Koralewski, Merwan Barlier, Yulia Stolin +1
Online recommendation platforms increasingly use Large Language Models (LLMs) to extract structured features from ad creatives. While deploying a single-call LLM annotation agent y…