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 "lstm easy first dependency parsing with pre trained word embeddings and character level word embeddings in vietnamese"):
  Abstract: In Vietnamese dependency parsing, several methods have been proposed. Dependency parser which uses deep neural network model has been reported that achieved state-of-the-art results. In this paper, we proposed a new method which applies LSTM easy-first dependency parsing with pre-trained word embeddings and character-level word embeddings. Our method achieves an accuracy of 80.91% of unlabeled attachment score and 72.98% of labeled attachment score on the Vietnamese Dependency Treebank (VnDT).

Includes members:
  Member "vietnamese transition based dependency parsing with supertag features":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a pilot study on multiple choice machine reading comprehension for vietnamese texts")
  Member "easy first dependency parsing with hierarchical tree lstms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep reinforcement learning for synthesizing functions in higher order logic")
  Member "an empirical study for vietnamese dependency parsing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a neural joint model for vietnamese word segmentation pos tagging and dependency parsing")
  Member "enriching word vectors with subword information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "simple and accurate dependency parsing using bidirectional lstm feature representations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parsing as pretraining")
  Member "improved transition based parsing by modeling characters instead of words with lstms":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transition based dependency parsing using perceptron learner")
  Member "transition based dependency parsing with stack long short term memory":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improving entity linking by modeling latent entity type information")
  Member "named entity recognition with bidirectional lstm cnns":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "monotonic cardinality estimation of similarity selection a deep learning approach")

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)