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 "data ordering patterns for neural machine translation an empirical study"):
  Abstract: Recent works show that ordering of the training data affects the model performance for Neural Machine Translation. Several approaches involving dynamic data ordering and data sharding based on curriculum learning have been analysed for the their performance gains and faster convergence. In this work we propose to empirically study several ordering approaches for the training data based on different metrics and evaluate their impact on the model performance. Results from our study show that pre-fixing the ordering of the training data based on perplexity scores from a pre-trained model performs the best and outperforms the default approach of randomly shuffling the training data every epoch.

Includes members:
  Member "competence based curriculum learning for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to inpaint by progressively growing the mask regions")
  Member "an empirical exploration of curriculum learning for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "curriculum learning strategies for ir an empirical study on conversation response ranking")
  Member "dynamic sentence sampling for efficient training of neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "head driven phrase structure grammar parsing on penn treebank")
  Member "automated curriculum learning for neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi source domain adaptation for text classification via distancenet bandits")
  Member "curriculum learning and minibatch bucketing in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to inpaint by progressively growing the mask regions")
  Member "sockeye a toolkit for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "marathi to english neural machine translation with near perfect corpus and transformers")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "dynamic data selection for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimizing data usage via differentiable rewards")

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)