9 citations · 12 across the 8 of their papers we have counts for
8 papers
Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training
Mingjie Liu, Shizhe Diao, Jian Hu +19
Recent advancements in reasoning-focused language models such as OpenAI's O1 and DeepSeek-R1 have shown that scaling test-time computation-through chain-of-thought reasoning and it…
Nowhere to Go: Benchmarking Multi-robot Collaboration in Target Trapping Environment
Hao Zhang, Jiaming Chen, Jiyu Cheng +3
Collaboration is one of the most important factors in multi-robot systems. Considering certain real-world applications and to further promote its development, we propose a new benc…
Learning Reconstructability for Drone Aerial Path Planning
Yilin Liu, Liqiang Lin, Yue Hu +4
We introduce the first learning-based reconstructability predictor to improve view and path planning for large-scale 3D urban scene acquisition using unmanned drones. In contrast t…
NAUTS: Negotiation for Adaptation to Unstructured Terrain Surfaces
Sriram Siva, Maggie Wigness, John G. Rogers +2
When robots operate in real-world off-road environments with unstructured terrains, the ability to adapt their navigational policy is critical for effective and safe navigation. Ho…
Adaptation to Team Composition Changes for Heterogeneous Multi-Robot Sensor Coverage
Brian Reily, Terran Mott, Hao Zhang
We consider the problem of multi-robot sensor coverage, which deals with deploying a multi-robot team in an environment and optimizing the sensing quality of the overall environmen…
Team Assignment for Heterogeneous Multi-Robot Sensor Coverage through Graph Representation Learning
Brian Reily, Hao Zhang
Sensor coverage is the critical multi-robot problem of maximizing the detection of events in an environment through the deployment of multiple robots. Large multi-robot systems are…