3 papers
cs.LG2026
Reliability Scaling Laws for Quantized Large Language Models
Sirine Ayadi, Sándor Daróczi, Stephan Günnemann +1
Quantization is a powerful strategy to build capable and resource-efficient large language models (LLMs) by reducing the bitwidth of the parameters. While quantized LLMs achieve st…
cs.LG2026
Interpolating Discrete Diffusion Models with Controllable Resampling
Marcel Kollovieh, Sirine Ayadi, Stephan Günnemann
Discrete diffusion models form a powerful class of generative models across diverse domains, including text and graphs. However, existing approaches face fundamental limitations. M…
q-bio.BM2025
Unified Guidance for Geometry-Conditioned Molecular Generation
Sirine Ayadi, Leon Hetzel, Johanna Sommer +2
Effectively designing molecular geometries is essential to advancing pharmaceutical innovations, a domain, which has experienced great attention through the success of generative m…