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 "adversarial example generation with syntactically controlled paraphrase networks"):
  Abstract: We propose syntactically controlled paraphrase networks (SCPNs) and use them to generate adversarial examples. Given a sentence and a target syntactic form (e.g., a constituency parse), SCPNs are trained to produce a paraphrase of the sentence with the desired syntax. We show it is possible to create training data for this task by first doing backtranslation at a very large scale, and then using a parser to label the syntactic transformations that naturally occur during this process. Such data allows us to train a neural encoder-decoder model with extra inputs to specify the target syntax. A combination of automated and human evaluations show that SCPNs generate paraphrases that follow their target specifications without decreasing paraphrase quality when compared to baseline (uncontrolled) paraphrase systems. Furthermore, they are more capable of generating syntactically adversarial examples that both (1) "fool" pretrained models and (2) improve the robustness of these models to syntactic variation when used to augment their training data.

Includes members:
  Member "deep text classification can be fooled":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "humpty dumpty controlling word meanings via corpus poisoning")
  Member "generating sentences by editing prototypes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue")
  Member "learning to paraphrase for question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "paraphrase generation with latent bag of words")
  Member "paranmt 50m pushing the limits of paraphrastic sentence embeddings with millions of machine translations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modelling latent skills for multitask language generation")
  Member "controlling linguistic style aspects in neural language generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "variational template machine for data to text generation")
  Member "learning paraphrastic sentence embeddings from back translated bitext":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "abstractive snippet generation")
  Member "steering output style and topic in neural response generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "non autoregressive neural dialogue generation")
  Member "a deep generative framework for paraphrase generation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "paraphrase generation with latent bag of words")

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)