3 papers
cs.CL2026
Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising
Dengyu Wu, Clement Ruah, Jiechen Chen +2
Autoregressive (AR) large language models (LLMs) are inherently inefficient at inference time because each generated token requires accessing the full set of model parameters, lead…
eess.SP2025
Context-Aware Doubly-Robust Semi-Supervised Learning
Clement Ruah, Houssem Sifaou, Osvaldo Simeone +1
The widespread adoption of artificial intelligence (AI) in next-generation communication systems is challenged by the heterogeneity of traffic and network conditions, which call fo…
cs.ET2024
Bayes2IMC: In-Memory Computing for Bayesian Binary Neural Networks
Prabodh Katti, Clement Ruah, Osvaldo Simeone +2
Bayesian Neural Networks (BNNs) provide superior estimates of uncertainty by generating an ensemble of predictive distributions. However, inference via ensembling is resource-inten…