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 "making sense of audio vibration for liquid height estimation in robotic pouring"):
  Abstract: In this paper, we focus on the challenging perception problem in robotic pouring. Most of the existing approaches either leverage visual or haptic information. However, these techniques may suffer from poor generalization performances on opaque containers or concerning measuring precision. To tackle these drawbacks, we propose to make use of audio vibration sensing and design a deep neural network PouringNet to predict the liquid height from the audio fragment during the robotic pouring task. PouringNet is trained on our collected real-world pouring dataset with multimodal sensing data, which contains more than 3000 recordings of audio, force feedback, video and trajectory data of the human hand that performs the pouring task. Each record represents a complete pouring procedure. We conduct several evaluations on PouringNet with our dataset and robotic hardware. The results demonstrate that our PouringNet generalizes well across different liquid containers, positions of the audio receiver, initial liquid heights and types of liquid, and facilitates a more robust and accurate audio-based perception for robotic pouring.

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 "learning to pour":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "perceiving and reasoning about liquids using fully convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "see the glass half full reasoning about liquid containers their volume and content":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "reasoning about liquids via closed loop simulation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "motion planning for fluid manipulation using simplified dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "to stir or not to stir online estimation of liquid properties for pouring actions")
  Member "visual closed loop control for pouring liquids":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust robotic pouring using audition and haptics")
  Member "deep residual learning for image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "discrimination aware network pruning for deep model compression")

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)