1. Paper 'To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers' accepted at ICML 2025.
2. Paper 'Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning' accepted at NAACL 2025.
3. Paper 'Revisiting Hierarchical Text Classification: Inference and Metrics' accepted at CoNLL 2024.
Research Experience
Currently a first-year Ph.D. student at Télécom Paris (part of IP Paris) and Onepoint.
Education
Ph.D. student at Télécom Paris (part of IP Paris) and Onepoint, supervised by Thomas Bonald, Matthieu Labeau, and Antoine Saillenfest; graduated from École des Ponts ParisTech in 2023 with a Master's degree in Mathematics, Vision, and Machine Learning (MVA) from ENS Paris-Saclay.
Background
Research interests: hierarchical classification, calibration, and optimal decision-making under uncertainty. Graduated from École des Ponts ParisTech and holds a master’s degree in Mathematics, Vision, and Machine Learning (MVA) from ENS Paris-Saclay.
Miscellany
Feel free to reach out for possible collaborations or questions regarding his research.