2 papers
cs.LG2026
Adapting the Behavior of Reinforcement Learning Agents to Changing Action Spaces and Reward Functions
Raul de la Rosa, Ivana Dusparic, Nicolas Cardozo
Reinforcement Learning (RL) agents often struggle in real-world applications where environmental conditions are non-stationary, particularly when reward functions shift or the avai…
cs.CL2025
A Hybrid Approach to Information Retrieval and Answer Generation for Regulatory Texts
Jhon Rayo, Raul de la Rosa, Mario Garrido
Regulatory texts are inherently long and complex, presenting significant challenges for information retrieval systems in supporting regulatory officers with compliance tasks. This…