activity
20242026
collaborators

20 papers

cs.LG2026

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models

Aleksandar Terzić, Francesco Carzaniga, Nicolas Menet +4

State-space models (SSMs) face a fundamental trade-off between efficiency and expressivity that is mainly dictated by the structure of the model's transition matrix. Unstructured t…

cs.CL2026

Locally Coherent Parallel Decoding in Diffusion Language Models

Michael Hersche, Nicolas Menet, Ronan Tanios +1

Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive (AR) models, offering sub-linear generation latency and bidirectional capabilities that a…

cs.LG2026

POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles

Nicolas Menet, Andreas Krause, Abbas Rahimi

Balancing exploration and exploitation is a core challenge in sequential decision-making and black-box optimization. We introduce POETS (licy nsembles for…

cs.SE2026

A Theoretical Analysis of Test-Driven Code Generation

Nicolas Menet, Michael Hersche, Andreas Krause +1

Code assistants are increasingly utilized in test-driven software development, yet the theoretical mechanisms behind their environment-interaction strategies remain underexplored.…

cs.LG2026

Soft-Masked Diffusion Language Models

Michael Hersche, Samuel Moor-Smith, Thomas Hofmann +1

Diffusion models have demonstrated strong potential in language modeling, offering various advantages over traditional autoregressive approaches. Their ability to generate and revi…

cs.LG2026

Thompson Sampling via Fine-Tuning of LLMs

Nicolas Menet, Aleksandar Terzić, Michael Hersche +2

Bayesian optimization in large unstructured discrete spaces is often hindered by the computational cost of maximizing acquisition functions due to the absence of gradients. We prop…