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 "analyzing sentence fusion in abstractive summarization"):
  Abstract: While recent work in abstractive summarization has resulted in higher scores in automatic metrics, there is little understanding on how these systems combine information taken from multiple document sentences. In this paper, we analyze the outputs of five state-of-the-art abstractive summarizers, focusing on summary sentences that are formed by sentence fusion. We ask assessors to judge the grammaticality, faithfulness, and method of fusion for summary sentences. Our analysis reveals that system sentences are mostly grammatical, but often fail to remain faithful to the original article.

Includes members:
  Member "hierarchical transformers for multi document summarization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bp transformer modelling long range context via binary partitioning")
  Member "discofuse a large scale dataset for discourse based sentence fusion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bert as a teacher contextual embeddings for sequence level reward")
  Member "what does bert look at an analysis of bert s attention":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "scoring sentence singletons and pairs for abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint parsing and generation for abstractive summarization")
  Member "deep communicating agents for abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "what is this article about extreme summarization with topic aware convolutional neural networks")
  Member "improving abstraction in text summarization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "avgout a simple output probability measure to eliminate dull responses")
  Member "bottom up abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "minilm deep self attention distillation for task agnostic compression of pre trained transformers")
  Member "toward abstractive summarization using semantic representations":
    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)