99 citations · 558 across the 65 of their papers we have counts for
69 papers
Barycentric Weak Inner-Product Gromov-Wasserstein
Youssef Mroueh
Gromov-Wasserstein (GW) compares distributions through relations within each space. This pointwise comparison can be too sensitive in one-to-many settings, where several target out…
Difference of Convex Programming in the Wasserstein Space with Applications to MMD Optimization
Clément Bonet, Pierre-Cyril Aubin-Frankowski, Youssef Mroueh
Optimizing functionals over the space of probability measures is now ubiquitous in machine learning. A widely used approach is to perform the optimization directly over the Wassers…
Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant
Nicolas Dupuis, Adarsh Tiwari, Youssef Mroueh +3
Qiskit is an open-source quantum computing framework that allows users to design, simulate, and run quantum circuits on real quantum hardware. We explore post-training techniques f…
GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidance
Jiri Navratil, Jarret Ross, Payel Das +4
The ability to design molecules while preserving similarity to a target molecule and/or property is crucial for various applications in drug discovery, chemical design, and biology…
Guided Speculative Inference for Efficient Test-Time Alignment of LLMs
Jonathan Geuter, Youssef Mroueh, David Alvarez-Melis
We propose Guided Speculative Inference (GSI), a novel algorithm for efficient reward-guided decoding in large language models. GSI combines soft best-of- test-time scaling with…
Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training
Youssef Mroueh, Nicolas Dupuis, Brian Belgodere +6
We revisit Group Relative Policy Optimization (GRPO) in both on-policy and off-policy optimization regimes. Our motivation comes from recent work on off-policy Proximal Policy Opti…