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 "gsn a graph structured network for multi party dialogues"):
  Abstract: Existing neural models for dialogue response generation assume that utterances are sequentially organized. However, many real-world dialogues involve multiple interlocutors (i.e., multi-party dialogues), where the assumption does not hold as utterances from different interlocutors can occur "in parallel." This paper generalizes existing sequence-based models to a Graph-Structured neural Network (GSN) for dialogue modeling. The core of GSN is a graph-based encoder that can model the information flow along the graph-structured dialogues (two-party sequential dialogues are a special case). Experimental results show that GSN significantly outperforms existing sequence-based models.

Includes members:
  Member "graph to sequence learning using gated graph neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "depth adaptive graph recurrent network for text classification")
  Member "addressee and response selection in multi party conversations with speaker interaction rnns":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "toward interpretability of dual encoder models for dialogue response suggestions")
  Member "emergence of language with multi agent games learning to communicate with sequences of symbols":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "assigning personality identity to a chatting machine for coherent conversation generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions")
  Member "dynamic routing between capsules":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lightweight residual densely connected convolutional neural network")
  Member "towards neural speaker modeling in multi party conversation the task dataset and models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "addressee and response selection in multi party conversations with speaker interaction rnns")
  Member "encoding sentences with graph convolutional networks for semantic role labeling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "benchmarking graph neural networks")
  Member "a persona based neural conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "non autoregressive neural dialogue generation")

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.CL(Computation and Language)