2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
WINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault Adaptation
Zahin Sufiyan, Shadan Golestan, Yoshihiro Mitsuka +2
Generative Flow Networks for continuous scenarios (CFlowNets) have shown promise in solving sequential decision-making tasks by learning stochastic policies using a flow and a retr…
The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning
Sheila Schoepp, Masoud Jafaripour, Yingyue Cao +6
Reinforcement learning (RL) has shown impressive results in sequential decision-making tasks. Meanwhile, Large Language Models (LLMs) and Vision-Language Models (VLMs) have emerged…
TLXML: Task-Level Explanation of Meta-Learning via Influence Functions
Yoshihiro Mitsuka, Shadan Golestan, Zahin Sufiyan +2
Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially regarding how past training tasks…
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms
Sheila Schoepp, Mehran Taghian, Shotaro Miwa +3
Industry is moving toward autonomous, network-connected machines that detect and adapt to changing conditions, including hardware faults. Conventional fault-tolerant design duplica…