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 "curriculum learning for domain adaptation in neural machine translation"):
  Abstract: We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of interest and each group is fed to the training algorithm with a particular schedule. This approach is simple to implement on top of any neural framework or architecture, and consistently outperforms both unadapted and adapted baselines in experiments with two distinct domains and two language pairs.

Includes members:
  Member "data selection with cluster based language difference models and cynical selection":
    also connected through other hyperedges:
      (none)
  Member "reinforcement learning based curriculum optimization for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimizing data usage via differentiable rewards")
  Member "competence based curriculum learning for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to inpaint by progressively growing the mask regions")
  Member "a survey of domain adaptation for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "curriculum learning by transfer learning theory and experiments with deep networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "curriculum learning for reinforcement learning domains a framework and survey")
  Member "denoising neural machine translation training with trusted data and online data selection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning a multitask curriculum for neural machine translation")
  Member "an empirical exploration of curriculum learning for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "curriculum learning strategies for ir an empirical study on conversation response ranking")
  Member "automated curriculum learning for neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi source domain adaptation for text classification via distancenet bandits")

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)