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 "task oriented dialog systems that consider multiple appropriate responses under the same context"):
  Abstract: Conversations have an intrinsic one-to-many property, which means that multiple responses can be appropriate for the same dialog context. In task-oriented dialogs, this property leads to different valid dialog policies towards task completion. However, none of the existing task-oriented dialog generation approaches takes this property into account. We propose a Multi-Action Data Augmentation (MADA) framework to utilize the one-to-many property to generate diverse appropriate dialog responses. Specifically, we first use dialog states to summarize the dialog history, and then discover all possible mappings from every dialog state to its different valid system actions. During dialog system training, we enable the current dialog state to map to all valid system actions discovered in the previous process to create additional state-action pairs. By incorporating these additional pairs, the dialog policy learns a balanced action distribution, which further guides the dialog model to generate diverse responses. Experimental results show that the proposed framework consistently improves dialog policy diversity, and results in improved response diversity and appropriateness. Our model obtains state-of-the-art results on MultiWOZ.

Includes members:
  Member "structured fusion networks for dialog":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hierarchical context enhanced multi domain dialogue system for multi domain task completion")
  Member "the curious case of neural text degeneration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "convlab multi domain end to end dialog system platform":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "rethinking action spaces for reinforcement learning in end to end dialog agents with latent variable models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "convlab 2 an open source toolkit for building evaluating and diagnosing dialogue systems")
  Member "semantically conditioned dialog response generation via hierarchical disentangled self attention":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "learning end to end goal oriented dialog with multiple answers":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "inset sentence infilling with inter sentential generative pre training")
  Member "hierarchical neural story generation":
    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 "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)