82 citations · 510 across the 22 of their papers we have counts for
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cs.LG2026
CEDAR: Context Engineering for Agentic Data Science
Rishiraj Saha Roy, Chris Hinze, Luzian Hahn +1
We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underexplored area that has immense market va…
cs.LG2019★ 81 cited
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
Azin Ghazimatin, Oana Balalau, Rishiraj Saha Roy +1
Interpretable explanations for recommender systems and other machine learning models are crucial to gain user trust. Prior works that have focused on paths connecting users and ite…