3 papers
cs.LG2026
Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
Lina Berrayana, Ahmed Heakl, Abdullah Sohail +3
Most multi-agent systems rely exclusively on autoregressive language models (ARMs) that are based on sequential generation. Although effective for fluent text, ARMs limit global re…
cs.CL2025
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
Lina Berrayana, Ahmed Heakl, Muhammad Abdullah Sohail +3
Current autoregressive language models (ARMs) achieve high accuracy but require long token sequences, making them costly. Discrete diffusion language models (DDLMs) enable parallel…
cs.AI2025
Are Bias Evaluation Methods Biased ?
Lina Berrayana, Sean Rooney, Luis Garcés-Erice +1
The creation of benchmarks to evaluate the safety of Large Language Models is one of the key activities within the trusted AI community. These benchmarks allow models to be compare…