3 accepted papers
Multimodal Large Language Models (MLLMs) show strong performance in Visual Question Answering (VQA) but remain limited in fine-grained reasoning due to low-resolution inputs and noisy attention aggregation. We propose \textbf{Head Aware Visual Cropping (HAVC)}, a training-free method that improves v…
Multi-agent reinforcement learning (MARL) meth-ods face a curse of dimensionality in the policy and value function representations as the number of agents increases. The development of distributed or parallel training techniques is also hindered by the global coupling among the agent dynamics, requi…
This paper aims to mitigate straggler effects in synchronous distributed learning for multi-agent reinforcement learning (MARL) problems. Stragglers arise frequently in a distributed learning system, due to the existence of various system disturbances such as slow-downs or failures of compute nodes…