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 "domain adaptive inference for neural machine translation"):
  Abstract: We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing performance on the original domain. We adapt sequentially across two Spanish-English and three English-German tasks, comparing unregularized fine-tuning, L2 and Elastic Weight Consolidation. We then report a novel scheme for adaptive NMT ensemble decoding by extending Bayesian Interpolation with source information, and show strong improvements across test domains without access to the domain label.

Includes members:
  Member "freezing subnetworks to analyze domain adaptation in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simple scalable adaptation for neural machine translation")
  Member "a call for clarity in reporting bleu scores":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "the university of edinburgh s neural mt systems for wmt17":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the linguistic representational power of neural machine translation models")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "sgnmt a flexible nmt decoding platform for quick prototyping of new models and search strategies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cued wmt19 ewc lms")
  Member "regularization techniques for fine tuning in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exploring benefits of transfer learning in neural machine translation")
  Member "six challenges for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "neural machine translation training in a multi domain scenario":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "tagged back 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)