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 "data augmentation with atomic templates for spoken language understanding"):
  Abstract: Spoken Language Understanding (SLU) converts user utterances into structured semantic representations. Data sparsity is one of the main obstacles of SLU due to the high cost of human annotation, especially when domain changes or a new domain comes. In this work, we propose a data augmentation method with atomic templates for SLU, which involves minimum human efforts. The atomic templates produce exemplars for fine-grained constituents of semantic representations. We propose an encoder-decoder model to generate the whole utterance from atomic exemplars. Moreover, the generator could be transferred from source domains to help a new domain which has little data. Experimental results show that our method achieves significant improvements on DSTC 2\&3 dataset which is a domain adaptation setting of SLU.

Includes members:
  Member "a hierarchical decoding model for spoken language understanding from unaligned data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dialogue history integration into end to end signal to concept spoken language understanding systems")
  Member "zero shot adaptive transfer for conversational language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fine tuning bert for schema guided zero shot dialogue state tracking")
  Member "data augmentation for spoken language understanding via joint variational generation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "variational hierarchical dialog autoencoder for dialogue state tracking data augmentation")
  Member "an end to end approach for handling unknown slot values in dialogue state tracking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "sequence to sequence data augmentation for dialogue language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "variational hierarchical dialog autoencoder for dialogue state tracking data augmentation")
  Member "towards zero shot frame semantic parsing for domain scaling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "zero resource cross domain named entity recognition")
  Member "concept transfer learning for adaptive language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "semantic parsing with dual learning")
  Member "pointing the unknown words":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "asking questions the human way scalable question answer generation from text corpus")

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)