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 "characterizing variation in crowd sourced data for training neural language generators to produce stylistically varied outputs"):
  Abstract: One of the biggest challenges of end-to-end language generation from meaning representations in dialogue systems is making the outputs more natural and varied. Here we take a large corpus of 50K crowd-sourced utterances in the restaurant domain and develop text analysis methods that systematically characterize types of sentences in the training data. We then automatically label the training data to allow us to conduct two kinds of experiments with a neural generator. First, we test the effect of training the system with different stylistic partitions and quantify the effect of smaller, but more stylistically controlled training data. Second, we propose a method of labeling the style variants during training, and show that we can modify the style of the generated utterances using our stylistic labels. We contrast and compare these methods that can be used with any existing large corpus, showing how they vary in terms of semantic quality and stylistic control.

Includes members:
  Member "dear sir or madam may i introduce the yafc corpus corpus benchmarks and metrics for formality style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "controlling linguistic style aspects in neural language generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "variational template machine for data to text generation")
  Member "harvesting creative templates for generating stylistically varied restaurant reviews":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "curate and generate a corpus and method for joint control of semantics and style in neural nlg")
  Member "the e2e dataset new challenges for end to end generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "few shot natural language generation for task oriented dialog")
  Member "crowd sourcing nlg data pictures elicit better data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "evaluating the state of the art of end to end natural language generation the e2e nlg challenge")
  Member "semantically conditioned lstm based natural language generation for spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "neural machine translation by jointly learning to align and translate":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "learning phrase representations using rnn encoder decoder for statistical machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transformation based adversarial video prediction on large scale data")

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)