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 "context aware learning for neural machine translation"):
  Abstract: Interest in larger-context neural machine translation, including document-level and multi-modal translation, has been growing. Multiple works have proposed new network architectures or evaluation schemes, but potentially helpful context is still sometimes ignored by larger-context translation models. In this paper, we propose a novel learning algorithm that explicitly encourages a neural translation model to take into account additional context using a multilevel pair-wise ranking loss. We evaluate the proposed learning algorithm with a transformer-based larger-context translation system on document-level translation. By comparing performance using actual and random contexts, we show that a model trained with the proposed algorithm is more sensitive to the additional context.

Includes members:
  Member "achieving human parity on automatic chinese to english news translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gret global representation enhanced transformer")
  Member "has machine translation achieved human parity a case for document level evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on document level machine translation methods and evaluation")
  Member "improving the transformer translation model with document level context":
    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 "document level neural machine translation with hierarchical attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "incorporating bert into neural machine translation")
  Member "the memad submission to the wmt18 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on architectures for including visual information in neural language models for image description")
  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 "learning to discriminate noises for incorporating external information in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on document level machine translation methods and evaluation")
  Member "extreme adaptation for personalized neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "machine translation system selection from bandit feedback")

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)