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 "neural simile recognition with cyclic multitask learning and local attention"):
  Abstract: Simile recognition is to detect simile sentences and to extract simile components, i.e., tenors and vehicles. It involves two subtasks: {\it simile sentence classification} and {\it simile component extraction}. Recent work has shown that standard multitask learning is effective for Chinese simile recognition, but it is still uncertain whether the mutual effects between the subtasks have been well captured by simple parameter sharing. We propose a novel cyclic multitask learning framework for neural simile recognition, which stacks the subtasks and makes them into a loop by connecting the last to the first. It iteratively performs each subtask, taking the outputs of the previous subtask as additional inputs to the current one, so that the interdependence between the subtasks can be better explored. Extensive experiments show that our framework significantly outperforms the current state-of-the-art model and our carefully designed baselines, and the gains are still remarkable using BERT.

Includes members:
  Member "open domain targeted sentiment analysis via span based extraction and classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "variational recurrent neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mixture content selection for diverse sequence generation")
  Member "a unified model for opinion target extraction and target sentiment prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "modeling localness for self attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gret global representation enhanced transformer")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "self attentional acoustic models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "context aware self attention networks")
  Member "variational neural discourse relation recognizer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "linguistic versus latent relations for modeling coherent flow in paragraphs")
  Member "variational neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mixpoet diverse poetry generation via learning controllable mixed latent space")

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)