15 citations · 20 across the 7 of their papers we have counts for
3 papers · 1 filter
LLM-Driven Intrinsic Motivation for Sparse Reward Reinforcement Learning
André Quadros, Cassio Silva, Ronnie Alves
This paper explores the combination of two intrinsic motivation strategies to improve the efficiency of reinforcement learning (RL) agents in environments with extreme sparse rewar…
Beyond Random Sampling: Instance Quality-Based Data Partitioning via Item Response Theory
Lucas Cardoso, Vitor Santos, José Ribeiro Filho +3
Robust validation of Machine Learning (ML) models is essential, but traditional data partitioning approaches often ignore the intrinsic quality of each instance. This study propose…
Enhancing Classifier Evaluation: A Fairer Benchmarking Strategy Based on Ability and Robustness
Lucas Cardoso, Vitor Santos, José Ribeiro +3
Benchmarking is a fundamental practice in machine learning (ML) for comparing the performance of classification algorithms. However, traditional evaluation methods often overlook a…