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 "goal embedded dual hierarchical model for task oriented dialogue generation"):
  Abstract: Hierarchical neural networks are often used to model inherent structures within dialogues. For goal-oriented dialogues, these models miss a mechanism adhering to the goals and neglect the distinct conversational patterns between two interlocutors. In this work, we propose Goal-Embedded Dual Hierarchical Attentional Encoder-Decoder (G-DuHA) able to center around goals and capture interlocutor-level disparity while modeling goal-oriented dialogues. Experiments on dialogue generation, response generation, and human evaluations demonstrate that the proposed model successfully generates higher-quality, more diverse and goal-centric dialogues. Moreover, we apply data augmentation via goal-oriented dialogue generation for task-oriented dialog systems with better performance achieved.

Includes members:
  Member "a repository of conversational datasets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient intent detection with dual sentence encoders")
  Member "simple fast accurate intent classification and slot labeling for goal oriented dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "diversity density and homogeneity quantitative characteristic metrics for text collections")
  Member "simple fast accurate intent classification and slot labeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cm net a novel collaborative memory network for spoken language understanding")
  Member "better conversations by modeling filtering and optimizing for coherence and diversity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "posterior gan towards informative and coherent response generation with posterior generative adversarial network")
  Member "data augmentation for spoken language understanding via joint variational generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "variational hierarchical dialog autoencoder for dialogue state tracking data augmentation")
  Member "a hierarchical latent structure for variational conversation modeling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "global locally self attentive dialogue state tracker":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "on the state of the art of evaluation in neural language models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

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)