human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "accurate robotic pouring for serving drinks"):
  Abstract: Pouring is the second most frequently executed motion in cooking scenarios. In this work, we present our system of accurate pouring that generates the angular velocities of the source container using recurrent neural networks. We collected demonstrations of human pouring water. We made a physical system on which the velocities of the source container were generated at each time step and executed by a motor. We tested our system on pouring water from containers that are not used for training and achieved an error of as low as 4 milliliters. We also used the system to pour oil and syrup. The accuracy achieved with oil is slightly lower than but comparable with that of water.

Includes members:
  Member "accurate pouring with an autonomous robot using an rgb d camera":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "functional object oriented network construction expansion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey of knowledge representation in service robotics")
  Member "a dataset of daily interactive manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "learning to pour":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "functional object oriented network for manipulation learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey of knowledge representation in service robotics")
  Member "visual closed loop control for pouring liquids":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "synthesis of recurrent neural networks for dynamical system simulation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "inferring dynamical systems with long range dependencies through line attractor regularization")
  Member "generating sequences with recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

Question: Please tell me which class the source paper 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)