I’m thrilled to share that I’ve finished my Ph.D. at Mila - Institut québécois d'IA. For the last 4.5 years, I have worked on creating new faithfulness-centric paradigms for NLP Interpretability. Read my vision for the future of interpretability in our newposition paper: arxiv.org/abs/2405.05386

Alice Gorgé just completed her research internship at the SCALE AI Chair in Polytechnique Mtl on the privacy risks of ML models. She has just received the prestigious Louis-Edouard Rivot medal, an honor given annually to École polytechnique (X) students who excel in their research work!😎

#ORMS #Analytics quietly powers decisions in healthcare, supply chains & beyond... yet is largely invisible to the public. Drawing inspiration from the growth of #ML, we outline 10 key actions to help move this status quo: pubsonline.informs.org/doi/full/10.12…. What else would you suggest?

The CVRPLIB introduces a new XL benchmark set (1,000–10,000 clients) along with a BKS challenge in January 2026. 30 days. One real-time leaderboard to compare modern methods: from classic OR and ML approaches, to learning-augmented hybrids and decomposition strategies...

Another interesting VRP challenge to keep an eye on 👀

A thought-provoking model of acceptance decisions in academic journals & conferences: slashing rates doesn't cut the eventual number of accepted papers, but it does delay good work, inflate visible submissions, and pile up reviewing/revision load: damaru2.github.io/general/queuei…

OCEAN is evolving 🌊, check it out! github.com/vidalt/OCEAN/ v2.0 offers a one-click Python library for optimal counterfactual explanations in tree ensembles (RFs, boosting...) based on MILP and CP models. Install with "pip install oceanpy". Unlike unstable heuristics that may