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 "inset sentence infilling with inter sentential generative pre training"):
  Abstract: Missing sentence generation (or sentence infilling) fosters a wide range of applications in natural language generation, such as document auto-completion and meeting note expansion. Such a task asks the model to generate intermediate missing sentence that can semantically and syntactically bridge the surrounding context. Solving the sentence infilling task requires techniques in NLP ranging from natural language understanding, discourse-level planning and natural language generation. In this paper, we present a framework to decouple this challenge and address these three aspects respectively, leveraging the power of existing large-scale pre-trained models such as BERT and GPT-2. Our empirical results demonstrate the effectiveness of our proposed model in learning a sentence representation for generation, and further generating a missing sentence that bridges the context.

Includes members:
  Member "tigs an inference algorithm for text infilling with gradient search":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "blank language models")
  Member "exploring the limits of transfer learning with a unified text to text transformer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on contextual embeddings")
  Member "linguistic versus latent relations for modeling coherent flow in paragraphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "automatic business process structure discovery using ordered neurons lstm a preliminary study")
  Member "the curious case of neural text degeneration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "what makes a good story designing composite rewards for visual storytelling":
    also connected through other hyperedges:
      (none)
  Member "spanbert improving pre training by representing and predicting spans":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on contextual embeddings")
  Member "abductive reasoning as self supervision for common sense question answering":
    also connected through other hyperedges:
      (none)
  Member "sentence bert sentence embeddings using siamese bert networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "contextual lensing of universal sentence representations")

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)