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 "resurrecting submodularity in neural abstractive summarization"):
  Abstract: Submodularity is a desirable property for a variety of objectives in summarization in terms of content selection where the encode-decoder framework is deficient. We propose `diminishing attentions', a class of novel attention mechanisms that are architecturally simple yet empirically effective to improve the coverage of neural abstractive summarization by exploiting the properties of submodular functions. Without adding any extra parameters to the Pointer-Generator baseline, our attention mechanism yields significant improvements in ROUGE scores and generates summaries of better quality. Our method within the Pointer-Generator framework outperforms the recently proposed Transformer model for summarization while using only 5 times less parameters. Our method also achieves state-of-the-art results in abstractive summarization when applied to the encoder-decoder attention in the Transformer model initialized with BERT.

Includes members:
  Member "bertscore evaluating text generation with bert":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on feature normalization and data augmentation")
  Member "moverscore text generation evaluating with contextualized embeddings and earth mover distance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bert as a teacher contextual embeddings for sequence level reward")
  Member "an entity driven framework for abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "discourse aware neural extractive model for text summarization")
  Member "text summarization with pretrained encoders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "bottom up abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minilm deep self attention distillation for task agnostic compression of pre trained transformers")
  Member "soft layer specific multi task summarization with entailment and question generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to multi task learn for better neural machine translation")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "fast abstractive summarization with reinforce selected sentence rewriting":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "structsum incorporating latent and explicit sentence dependencies for single document summarization")

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)