14 papers
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…
Structurally Separated Uncertainty in Supervised Latent Variable Models
Tanmoy Mukherjee, Marius Kloft, Pierre Marquis +1
Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated estimates because both quantiti…