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 "teacher student framework enhanced multi domain dialogue generation"):
  Abstract: Dialogue systems dealing with multi-domain tasks are highly required. How to record the state remains a key problem in a task-oriented dialogue system. Normally we use human-defined features as dialogue states and apply a state tracker to extract these features. However, the performance of such a system is limited by the error propagation of a state tracker. In this paper, we propose a dialogue generation model that needs no external state trackers and still benefits from human-labeled semantic data. By using a teacher-student framework, several teacher models are firstly trained in their individual domains, learn dialogue policies from labeled states. And then the learned knowledge and experience are merged and transferred to a universal student model, which takes raw utterance as its input. Experiments show that the dialogue system trained under our framework outperforms the one uses a belief tracker.

Includes members:
  Member "multilingual neural machine translation with knowledge distillation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "flexible and scalable state tracking framework for goal oriented dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dialogact2vec towards end to end dialogue agent by multi task representation learning")
  Member "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "toward scalable neural dialogue state tracking model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "variational hierarchical dialog autoencoder for dialogue state tracking data augmentation")
  Member "scalable multi domain dialogue state tracking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non autoregressive dialog state tracking")
  Member "multi domain neural network language generation for spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "neural belief tracker data driven dialogue state tracking":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "a hierarchical latent variable encoder decoder model for generating dialogues":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "attention over parameters for dialogue systems")

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)