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 "a simple lstm model for transition based dependency parsing"):
  Abstract: We present a simple LSTM-based transition-based dependency parser. Our model is composed of a single LSTM hidden layer replacing the hidden layer in the usual feed-forward network architecture. We also propose a new initialization method that uses the pre-trained weights from a feed-forward neural network to initialize our LSTM-based model. We also show that using dropout on the input layer has a positive effect on performance. Our final parser achieves a 93.06% unlabeled and 91.01% labeled attachment score on the Penn Treebank. We additionally replace LSTMs with GRUs and Elman units in our model and explore the effectiveness of our initialization method on individual gates constituting all three types of RNN units.

Includes members:
  Member "easy first dependency parsing with hierarchical tree lstms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep reinforcement learning for synthesizing functions in higher order logic")
  Member "globally normalized transition based neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "consistency of a recurrent language model with respect to incomplete decoding")
  Member "simple and accurate dependency parsing using bidirectional lstm feature representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "parsing as pretraining")
  Member "dependency parsing with lstms an empirical evaluation":
    also connected through other hyperedges:
      (none)
  Member "a simple way to initialize recurrent networks of rectified linear units":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "refined gate a simple and effective gating mechanism for recurrent units")
  Member "transition based dependency parsing with stack long short term memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving entity linking by modeling latent entity type information")
  Member "top down tree long short term memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hierarchical character embeddings learning phonological and semantic representations in languages of logographic origin using recursive neural networks")
  Member "structured training for neural network transition based parsing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "concurrent parsing of constituency and dependency")

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)