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 "retrieval based goal oriented dialogue generation"):
  Abstract: Most research on dialogue has focused either on dialogue generation for openended chit chat or on state tracking for goal-directed dialogue. In this work, we explore a hybrid approach to goal-oriented dialogue generation that combines retrieval from past history with a hierarchical, neural encoder-decoder architecture. We evaluate this approach in the customer support domain using the Multiwoz dataset (Budzianowski et al., 2018). We show that adding this retrieval step to a hierarchical, neural encoder-decoder architecture leads to significant improvements, including responses that are rated more appropriate and fluent by human evaluators. Finally, we compare our retrieval-based model to various semantically conditioned models explicitly using past dialog act information, and find that our proposed model is competitive with the current state of the art (Chen et al., 2019), while not requiring explicit labels about past machine acts.

Includes members:
  Member "scaling multi domain dialogue state tracking via query reformulation":
    also connected through other hyperedges:
      (none)
  Member "semantically conditioned dialog response generation via hierarchical disentangled self attention":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "on extractive and abstractive neural document summarization with transformer language models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep reinforced self attention masks for abstractive summarization dr sas")
  Member "retrieve and refine improved sequence generation models for dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the second conversational intelligence challenge convai2")
  Member "towards universal dialogue state tracking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "a strong baseline for question relevancy ranking":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bertsel answer selection with pre trained models")
  Member "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "sequence to sequence learning for task oriented dialogue with dialogue state representation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")

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)