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 "a survey of available corpora for building data driven dialogue systems"):
  Abstract: During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge. Nevertheless, several recent results suggest that data-driven approaches are feasible and quite promising. To facilitate research in this area, we have carried out a wide survey of publicly available datasets suitable for data-driven learning of dialogue systems. We discuss important characteristics of these datasets and how they can be used to learn diverse dialogue strategies. We also describe other potential uses of these datasets, such as methods for transfer learning between datasets and the use of external knowledge, and discuss appropriate choice of evaluation metrics for the learning objective.

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 "tweet2vec character based distributed representations for social media":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "maskdga a black box evasion technique against dga classifiers and adversarial defenses")
  Member "natural language generation in dialogue using lexicalized and delexicalized data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "evaluating the state of the art of end to end natural language generation the e2e nlg challenge")
  Member "multiresolution recurrent neural networks an application to dialogue response generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "avgout a simple output probability measure to eliminate dull responses")
  Member "multi domain neural network language generation for spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "end to end lstm based dialog control optimized with supervised and reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dialogact2vec towards end to end dialogue agent by multi task representation learning")
  Member "dialog based language learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "pseudo labeling and negative feedback learning for large scale multi label domain classification")
  Member "ms marco a human generated machine reading comprehension dataset":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a study of the tasks and models in machine reading comprehension")

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)