human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "baxter s homunculus virtual reality spaces for teleoperation in manufacturing"
  Abstract: Expensive specialized systems have hampered development of telerobotic systems for manufacturing systems. In this paper we demonstrate a telerobotic system which can reduce the cost of such system by leveraging commercial virtual reality(VR) technology and integrating it with existing robotics control software. The system runs on a commercial gaming engine using off the shelf VR hardware. This system can be deployed on multiple network architectures from a wired local network to a wireless network connection over the Internet. The system is based on the homunculus model of mind wherein we embed the user in a virtual reality control room. The control room allows for multiple sensor display, dynamic mapping between the user and robot, does not require the production of duals for the robot, or its environment. The control room is mapped to a space inside the robot to provide a sense of co-location within the robot. We compared our system with state of the art automation algorithms for assembly tasks, showing a 100% success rate for our system compared with a 66% success rate for automated systems. We demonstrate that our system can be used for pick and place, assembly, and manufacturing tasks.

Connected through hyperedge HE-1 (induced by source paper "scaling robot supervision to hundreds of hours with roboturk robotic manipulation dataset through human reasoning and dexterity"):
  with members:
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"
    - "playing hard exploration games by watching youtube"
    - "know what you don t know unanswerable questions for squad"
    - "sim to real via sim to sim data efficient robotic grasping via randomized to canonical adaptation networks"
    - "roboturk a crowdsourcing platform for robotic skill learning through imitation"
    - "one shot imitation from observing humans via domain adaptive meta learning"
    - "multiple interactions made easy mime large scale demonstrations data for imitation"
    - "leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards"

Connected through hyperedge HE-2 (induced by source paper "time series motion generation considering long short term motion"):
  with members:
    - "imitation learning for object manipulation based on position force information using bilateral control"
    - "deep imitation learning for complex manipulation tasks from virtual reality teleoperation"
    - "learning hand eye coordination for robotic grasping with deep learning and large scale data collection"
    - "fast and accurate recurrent neural network acoustic models for speech recognition"
    - "sequence level training with recurrent neural networks"
    - "scheduled sampling for sequence prediction with recurrent neural networks"
    - "translating videos to natural language using deep recurrent neural networks"

Connected through hyperedge HE-3 (induced by source paper "human intention estimation based on hidden markov model motion validation for safe flexible robotized warehouses"):
  with members:
    - "human intention recognition in flexible robotized warehouses based on markov decision processes"
    - "deep imitation learning for complex manipulation tasks from virtual reality teleoperation"
    - "virtual borders accurate definition of a mobile robot s workspace using a rgb d google tango tablet"
    - "past present and future of simultaneous localization and mapping toward the robust perception age"
    - "capir collaborative action planning with intention recognition"

Connected through hyperedge HE-4 (induced by source paper "a vr system for immersive teleoperation and live exploration with a mobile robot"):
  with members:
    - "slamcast large scale real time 3d reconstruction and streaming for immersive multi client live telepresence"
    - "team nimbro at mbzirc 2017 autonomous valve stem turning using a wrench"
    - "supervised autonomous locomotion and manipulation for disaster response with a centaur like robot"

Connected through hyperedge HE-5 (induced by source paper "using socially expressive mixed reality arms for enhancing low expressivity robots"):
  with members:
    - "embodiment in socially interactive robots"
    - "deep imitation learning for complex manipulation tasks from virtual reality teleoperation"

Connected through hyperedge HE-6 (induced by source paper "roboturk a crowdsourcing platform for robotic skill learning through imitation"):
  with members:
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"
    - "backplay man muss immer umkehren"
    - "learning task oriented grasping for tool manipulation from simulated self supervision"
    - "reinforcement and imitation learning for diverse visuomotor skills"
    - "know what you don t know unanswerable questions for squad"
    - "leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards"
    - "dex net 2 0 deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics"
    - "overcoming exploration in reinforcement learning with demonstrations"

Connected through hyperedge HE-7 (induced by source paper "annotation scaffolds for object modeling and manipulation"):
  with members:
    - "a robust 3d 2d interactive tool for scene segmentation and annotation"
    - "shapenet an information rich 3d model repository"
    - "robobarista object part based transfer of manipulation trajectories from crowd sourcing in 3d pointclouds"
    - "data driven grasp synthesis a survey"
    - "visualizing and understanding convolutional networks"
    - "toric degenerations of bezier patches"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.RO(Robotics)