12 citations · 22 across the 4 of their papers we have counts for
4 papers
Interpretable Tabular Foundation Models via In-Context Kernel Regression
Ratmir Miftachov, Bruno Charron, Simon Valentin
Tabular foundation models like TabPFN and TabICL achieve state-of-the-art performance through in-context learning, yet their architectures remain fundamentally opaque. We introduce…
MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation
María Andrea Cruz Blandón, Jayasimha Talur, Bruno Charron +3
Automatic evaluation of retrieval augmented generation (RAG) systems relies on fine-grained dimensions like faithfulness and relevance, as judged by expert human annotators. Meta-e…
Large-scale Recommendation for Portfolio Optimization
Robin Swezey, Bruno Charron
Individual investors are now massively using online brokers to trade stocks with convenient interfaces and low fees, albeit losing the advice and personalization traditionally prov…
PiRank: Scalable Learning To Rank via Differentiable Sorting
Robin Swezey, Aditya Grover, Bruno Charron +1
A key challenge with machine learning approaches for ranking is the gap between the performance metrics of interest and the surrogate loss functions that can be optimized with grad…