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 dependency based neural reordering model for statistical machine translation"):
  Abstract: In machine translation (MT) that involves translating between two languages with significant differences in word order, determining the correct word order of translated words is a major challenge. The dependency parse tree of a source sentence can help to determine the correct word order of the translated words. In this paper, we present a novel reordering approach utilizing a neural network and dependency-based embeddings to predict whether the translations of two source words linked by a dependency relation should remain in the same order or should be swapped in the translated sentence. Experiments on Chinese-to-English translation show that our approach yields a statistically significant improvement of 0.57 BLEU point on benchmark NIST test sets, compared to our prior state-of-the-art statistical MT system that uses sparse dependency-based reordering features.

Includes members:
  Member "memory enhanced decoder for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "training simplification and model simplification for deep learning a minimal effort back propagation method")
  Member "is neural machine translation ready for deployment a case study on 30 translation directions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cued wmt19 ewc lms")
  Member "to swap or not to swap exploiting dependency word pairs for reordering in statistical machine translation":
    also connected through other hyperedges:
      (none)
  Member "lstm neural reordering feature for statistical machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "using an ancillary neural network to capture weekends and holidays in an adjoint neural network architecture for intelligent building management")
  Member "globally normalized transition based neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "consistency of a recurrent language model with respect to incomplete decoding")
  Member "variational neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)