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 "towards neural speaker modeling in multi party conversation the task dataset and models"):
  Abstract: Neural network-based dialog systems are attracting increasing attention in both academia and industry. Recently, researchers have begun to realize the importance of speaker modeling in neural dialog systems, but there lacks established tasks and datasets. In this paper, we propose speaker classification as a surrogate task for general speaker modeling, and collect massive data to facilitate research in this direction. We further investigate temporal-based and content-based models of speakers, and propose several hybrids of them. Experiments show that speaker classification is feasible, and that hybrid models outperform each single component.

Includes members:
  Member "hierarchical rnn with static sentence level attention for text based speaker change detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved hierarchical patient classification with language model pretraining over clinical notes")
  Member "sequence to backward and forward sequences a content introducing approach to generative short text conversation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non autoregressive neural dialogue generation")
  Member "building end to end dialogue systems using generative hierarchical neural network models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "attention over parameters for dialogue systems")
  Member "the ubuntu dialogue corpus a large dataset for research in unstructured multi turn dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "toward interpretability of dual encoder models for dialogue response suggestions")
  Member "a neural network approach to context sensitive generation of conversational responses":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non autoregressive neural dialogue generation")
  Member "neural responding machine for short text conversation":
    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 "attention with intention for a neural network conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions")
  Member "adam a method for stochastic optimization":
    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)