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: "voxml a visualization modeling language"
  Abstract: We present the specification for a modeling language, VoxML, which encodes semantic knowledge of real-world objects represented as three-dimensional models, and of events and attributes related to and enacted over these objects. VoxML is intended to overcome the limitations of existing 3D visual markup languages by allowing for the encoding of a broad range of semantic knowledge that can be exploited by a variety of systems and platforms, leading to multimodal simulations of real-world scenarios using conceptual objects that represent their semantic values.

Connected through hyperedge HE-1 (induced by source paper "a formal analysis of multimodal referring strategies under common ground"):
  with members:
    - "grounding language attributes to objects using bayesian eigenobjects"
    - "generating justifications for norm related agent decisions"
    - "multimodal attention branch network for perspective free sentence generation"
    - "multimodal continuation style architectures for human robot interaction"
    - "interactive visual grounding of referring expressions for human robot interaction"
    - "neuralreg an end to end approach to referring expression generation"
    - "multimodal grounding for language processing"
    - "a visual attention grounding neural model for multimodal machine translation"

Connected through hyperedge HE-2 (induced by source paper "multimodal continuation style architectures for human robot interaction"):
  with members:
    - "situational grounding within multimodal simulations"
    - "multimodal semantic simulations of linguistically underspecified motion events"

Connected through hyperedge HE-3 (induced by source paper "situational grounding within multimodal simulations"):
  with members:
    - "combining deep learning and qualitative spatial reasoning to learn complex structures from sparse examples with noise"

Connected through hyperedge HE-4 (induced by source paper "combining deep learning and qualitative spatial reasoning to learn complex structures from sparse examples with noise"):
  with members:
    - "grounded language learning in a simulated 3d world"
    - "embodied question answering"
    - "unsupervised human action detection by action matching"
    - "unsupervised learning from narrated instruction videos"
    - "convolutional neural network architectures for matching natural language sentences"
    - "simultaneous object detection tracking and event recognition"

Connected through hyperedge HE-5 (induced by source paper "multimodal semantic simulations of linguistically underspecified motion events"):
  with members:
    - "fine grained event learning of human object interaction with lstm crf"
    - "ecat event capture annotation tool"
    - "globally normalized transition based neural networks"
    - "generating simulations of motion events from verbal descriptions"
    - "text to 3d scene generation with rich lexical grounding"
    - "grounding the lexical semantics of verbs in visual perception using force dynamics and event logic"

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.CL(Computation and Language)