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 transformer unpaired text style transfer without disentangled latent representation"):
  Abstract: Disentangling the content and style in the latent space is prevalent in unpaired text style transfer. However, two major issues exist in most of the current neural models. 1) It is difficult to completely strip the style information from the semantics for a sentence. 2) The recurrent neural network (RNN) based encoder and decoder, mediated by the latent representation, cannot well deal with the issue of the long-term dependency, resulting in poor preservation of non-stylistic semantic content. In this paper, we propose the Style Transformer, which makes no assumption about the latent representation of source sentence and equips the power of attention mechanism in Transformer to achieve better style transfer and better content preservation.

Includes members:
  Member "transformer xl attentive language models beyond a fixed length context":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on contextual embeddings")
  Member "imat unsupervised text attribute transfer via iterative matching and translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "is bert really robust a strong baseline for natural language attack on text classification and entailment")
  Member "style transfer as unsupervised machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "imat unsupervised text attribute transfer via iterative matching and translation")
  Member "disentangled representation learning for non parallel text style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "delete retrieve generate a simple approach to sentiment and style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")
  Member "shaped shared private encoder decoder for text style adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "domain adaptive text style transfer")
  Member "fighting offensive language on social media with unsupervised text style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "pots protective optimization technologies")

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)