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 "enhancing context modeling with a query guided capsule network for document level translation"):
  Abstract: Context modeling is essential to generate coherent and consistent translation for Document-level Neural Machine Translations. The widely used method for document-level translation usually compresses the context information into a representation via hierarchical attention networks. However, this method neither considers the relationship between context words nor distinguishes the roles of context words. To address this problem, we propose a query-guided capsule networks to cluster context information into different perspectives from which the target translation may concern. Experiment results show that our method can significantly outperform strong baselines on multiple data sets of different domains.

Includes members:
  Member "bridging the gap between training and inference for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discriminative adversarial search for abstractive summarization")
  Member "selective attention for context aware neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "toward making the most of context in neural machine translation")
  Member "modeling coherence for discourse neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capturing document context inside sentence level neural machine translation models with self training")
  Member "improving the transformer translation model with document level context":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capturing document context inside sentence level neural machine translation models with self training")
  Member "dtmt a novel deep transition architecture for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "making neural machine reading comprehension faster")
  Member "context aware neural machine translation learns anaphora resolution":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "toward making the most of context in neural machine translation")
  Member "towards linear time neural machine translation with capsule networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gret global representation enhanced transformer")
  Member "neural machine translation with extended context":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multilingual denoising pre training for neural machine translation")

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)