2 citations · 2 across the 4 of their papers we have counts for
5 papers
RL-VLA: Adaptive RL Latent Compositional Steering with Test-Time Scaling for Vision-Language-Action Models
Derek Ming Siang Tan, Shailesh Shailesh, Srikrishna Iyer +4
Despite the impressive visuomotor capabilities enabled by Vision-Language-Action (VLA) models, their performance often degrades on challenging and out-of-domain tasks. Recent test-…
ORION: Option-Regularized Deep Reinforcement Learning for Cooperative Multi-Agent Online Navigation
Shizhe Zhang, Jingsong Liang, Zhitao Zhou +6
Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with outdated or imperfect prior maps,…
AID: Agent Intent from Diffusion for Multi-Agent Informative Path Planning
Jeric Lew, Yuhong Cao, Derek Ming Siang Tan +1
Information gathering in large-scale or time-critical scenarios (e.g., environmental monitoring, search and rescue) requires broad coverage within limited time budgets, motivating…
IR2: Implicit Rendezvous for Robotic Exploration Teams under Sparse Intermittent Connectivity
Derek Ming Siang Tan, Yixiao Ma, Jingsong Liang +3
Information sharing is critical in time-sensitive and realistic multi-robot exploration, especially for smaller robotic teams in large-scale environments where connectivity may be…
Privileged Reinforcement and Communication Learning for Distributed, Bandwidth-limited Multi-robot Exploration
Yixiao Ma, Jingsong Liang, Yuhong Cao +2
Communication bandwidth is an important consideration in multi-robot exploration, where information exchange among robots is critical. While existing methods typically aim to reduc…