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 "topic augmented neural network for short text conversation"):
  Abstract: Message response matching is an important task within retrieval-based chatbots. We present a topic augmented neural network(TANN), comprising a sentence embedding layer, a topic embedding layer, and a matching layer, to match messages and response candidates. TANN inherits the benefits of neutral networks on matching sentence pairs, and leverages extra topic information and their corresponding weights as prior knowledge into a matching process. In TANN, the sentence embedding layer embeds an input message and a response into a vector space, while the topic embedding layer forms a topic vector by a linear combination of the embedding of topic words whose weights are determined by both themselves and the message vector. The message vector, the response vector, and the topic vector are then fed to the matching layer to calculate a matching score. The extensive evaluation of TANN, using large human annotated data sets, shows that TANN outperforms simple neutral network methods, while beating other typical matching models with a large margin.

Includes members:
  Member "a persona based neural conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "non autoregressive neural dialogue generation")
  Member "incorporating loose structured knowledge into conversation modeling via recall gate lstm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "conversation generation with concept flow")
  Member "text matching as image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "selective weak supervision for neural information retrieval")
  Member "syntax based deep matching of short texts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unsupervised context rewriting for open domain conversation")
  Member "building end to end dialogue systems using generative hierarchical neural network models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "attention over parameters for dialogue systems")
  Member "the ubuntu dialogue corpus a large dataset for research in unstructured multi turn dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "toward interpretability of dual encoder models for dialogue response suggestions")
  Member "convolutional neural network architectures for matching natural language sentences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "selective weak supervision for neural information retrieval")
  Member "a neural network approach to context sensitive generation of conversational responses":
    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)