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 "controllable paraphrase generation with a syntactic exemplar"):
  Abstract: Prior work on controllable text generation usually assumes that the controlled attribute can take on one of a small set of values known a priori. In this work, we propose a novel task, where the syntax of a generated sentence is controlled rather by a sentential exemplar. To evaluate quantitatively with standard metrics, we create a novel dataset with human annotations. We also develop a variational model with a neural module specifically designed for capturing syntactic knowledge and several multitask training objectives to promote disentangled representation learning. Empirically, the proposed model is observed to achieve improvements over baselines and learn to capture desirable characteristics.

Includes members:
  Member "a multi task approach for disentangling syntax and semantics in sentence representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compound probabilistic context free grammars for grammar induction")
  Member "toward unsupervised text content manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "select and attend towards controllable content selection in text generation")
  Member "text generation with exemplar based adaptive decoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low resource response generation with template prior")
  Member "smaller text classifiers with discriminative cluster embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "latent variable generative models for data efficient text classification")
  Member "variational sequential labelers for semi supervised learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards generating long and coherent text with multi level latent variable models")
  Member "towards generating long and coherent text with multi level latent variable models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a unified system for aggression identification in english code mixed and uni lingual texts")
  Member "retrieve and refine improved sequence generation models for dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the second conversational intelligence challenge convai2")
  Member "disentangled representation learning for non parallel text style transfer":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to generate multiple style transfer outputs for an input sentence")

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)