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 "discourse aware neural rewards for coherent text generation"):
  Abstract: In this paper, we investigate the use of discourse-aware rewards with reinforcement learning to guide a model to generate long, coherent text. In particular, we propose to learn neural rewards to model cross-sentence ordering as a means to approximate desired discourse structure. Empirical results demonstrate that a generator trained with the learned reward produces more coherent and less repetitive text than models trained with cross-entropy or with reinforcement learning with commonly used scores as rewards.

Includes members:
  Member "reinforced video captioning with entailment rewards":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "delving deeper into the decoder for video captioning")
  Member "improved image captioning via policy gradient optimization of spider":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "deep reinforcement learning based image captioning with embedding reward":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "towards an automatic turing test learning to evaluate dialogue responses":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards a human like open domain chatbot")
  Member "simulating action dynamics with neural process networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "recipegpt generative pre training based cooking recipe generation and evaluation system")
  Member "challenges in data to document generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "variational template machine for data to text generation")
  Member "paraphrase generation with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "paraphrase generation with latent bag of words")
  Member "a deep reinforced model for abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "time aware large kernel convolutions")

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)