1 citations · 1 across the 18 of their papers we have counts for
16 papers
Dense Structural Compression of Transformers via Gauge-Correct Channel Removal
Jed A. Duersch, Naïm Es-Sebbani, Nathanaël Haas +1
Inference energy per token drives the cost and carbon footprint of deployed transformers. It is dominated by dense matrix products that incur fused multiply-accumulate (FMA) operat…
Explanation Quality Assessment as Ranking with Listwise Rewards
Thomas Bailleux, Tanmoy Mukherjee, Emmanuel Lonca +2
We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single "best" explanation token-by-to…
Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition
Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis +1
Concept Bottleneck Models (CBMs) predict through human-interpretable concepts, but they typically output point concept probabilities that conflate epistemic uncertainty (reducible…
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Nathanaël Haas, François Gatine, Augustin M Cosse +1
Understanding why gradient-based training in deep networks exhibits strong implicit bias remains challenging, in part because tractable singular-value dynamics are typically availa…
Evaluating Robustness of Reasoning Models on Parameterized Logical Problems
Naïm Es-sebbani, Esteban Marquer, Yakoub Salhi +1
Logic provides a controlled testbed for evaluating LLM-based reasoners, yet standard SAT-style benchmarks often conflate surface difficulty (length, wording, clause order) with the…
Fourier Transformers for Latent Crystallographic Diffusion and Generative Modeling
Jed A. Duersch, Elohan Veillon, Astrid Klipfel +2
The discovery of new crystalline materials calls for generative models that handle periodic boundary conditions, crystallographic symmetries, and physical constraints, while scalin…