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 "style transfer as unsupervised machine translation"):
  Abstract: Language style transferring rephrases text with specific stylistic attributes while preserving the original attribute-independent content. One main challenge in learning a style transfer system is a lack of parallel data where the source sentence is in one style and the target sentence in another style. With this constraint, in this paper, we adapt unsupervised machine translation methods for the task of automatic style transfer. We first take advantage of style-preference information and word embedding similarity to produce pseudo-parallel data with a statistical machine translation (SMT) framework. Then the iterative back-translation approach is employed to jointly train two neural machine translation (NMT) based transfer systems. To control the noise generated during joint training, a style classifier is introduced to guarantee the accuracy of style transfer and penalize bad candidates in the generated pseudo data. Experiments on benchmark datasets show that our proposed method outperforms previous state-of-the-art models in terms of both accuracy of style transfer and quality of input-output correspondence.

Includes members:
  Member "delete retrieve generate a simple approach to sentiment and 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 "style transfer through back translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "phrase based neural unsupervised machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "unpaired sentiment to sentiment translation a cycled reinforcement learning approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "toward controlled generation of text":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust explanations for visual question answering")
  Member "style transfer from non parallel text by cross alignment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "unsupervised machine translation using monolingual corpora only":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "unsupervised question decomposition for question answering")
  Member "unsupervised neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multilingual denoising pre training for neural machine translation")

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)