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 network based end to end trainable task oriented dialogue system"):
  Abstract: Teaching machines to accomplish tasks by conversing naturally with humans is challenging. Currently, developing task-oriented dialogue systems requires creating multiple components and typically this involves either a large amount of handcrafting, or acquiring costly labelled datasets to solve a statistical learning problem for each component. In this work we introduce a neural network-based text-in, text-out end-to-end trainable goal-oriented dialogue system along with a new way of collecting dialogue data based on a novel pipe-lined Wizard-of-Oz framework. This approach allows us to develop dialogue systems easily and without making too many assumptions about the task at hand. The results show that the model can converse with human subjects naturally whilst helping them to accomplish tasks in a restaurant search domain.

Includes members:
  Member "multi domain neural network language generation for spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "on line active reward learning for policy optimisation in spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "latent predictor networks for code generation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi modal attention network learning for semantic source code retrieval")
  Member "end to end memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning video object segmentation from unlabeled videos")
  Member "a survey of available corpora for building data driven dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the apiza corpus api usage dialogues with a simulated virtual assistant")
  Member "multi domain dialog state tracking using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "neural responding machine for short text conversation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "learning from real users rating dialogue success with neural networks for reinforcement learning in spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "improving interaction quality estimation with bilstms and the impact on dialogue policy learning")

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)