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 "learning rhyming constraints using structured adversaries"):
  Abstract: Existing recurrent neural language models often fail to capture higher-level structure present in text: for example, rhyming patterns present in poetry. Much prior work on poetry generation uses manually defined constraints which are satisfied during decoding using either specialized decoding procedures or rejection sampling. The rhyming constraints themselves are typically not learned by the generator. We propose an alternate approach that uses a structured discriminator to learn a poetry generator that directly captures rhyming constraints in a generative adversarial setup. By causing the discriminator to compare poems based only on a learned similarity matrix of pairs of line ending words, the proposed approach is able to successfully learn rhyming patterns in two different English poetry datasets (Sonnet and Limerick) without explicitly being provided with any phonetic information.

Includes members:
  Member "answer based adversarial training for generating clarification questions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "asking clarifying questions in open domain information seeking conversations")
  Member "discourse aware neural rewards for coherent text generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non autoregressive neural dialogue generation")
  Member "learning to write with cooperative discriminators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bert as a teacher contextual embeddings for sequence level reward")
  Member "deep speare a joint neural model of poetic language meter and rhyme":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "introducing aspects of creativity in automatic poetry generation")
  Member "neural dynamic programming for musical self similarity":
    also connected through other hyperedges:
      (none)
  Member "no metrics are perfect adversarial reward learning for visual storytelling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "paraphrase generation with latent bag of words")
  Member "sentence simplification with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generative question refinement with deep reinforcement learning in retrieval based qa system")
  Member "deep reinforcement learning for dialogue generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")

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)