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 "future prediction based model for neural machine translation"):
  Abstract: We propose a novel model for Neural Machine Translation (NMT). Different from the conventional method, our model can predict the future text length and words at each decoding time step so that the generation can be helped with the information from the future prediction. With such information, the model does not stop generation without having translated enough content. Experimental results demonstrate that our model can significantly outperform the baseline models. Besides, our analysis reflects that our model is effective in the prediction of the length and words of the untranslated content.

Includes members:
  Member "decoding history based adaptive control of attention for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deconvolution based global decoding for neural machine translation")
  Member "bag of words as target for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "paraphrase generation with latent bag of words")
  Member "learning when to concentrate or divert attention self adaptive attention temperature for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explicit sparse transformer concentrated attention through explicit selection")
  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 "multi channel encoder for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi layer representation fusion for neural machine translation")
  Member "coverage embedding models for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "modeling future cost for neural machine translation")
  Member "interactive attention for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improving multi head attention with capsule networks")
  Member "neural machine translation in linear time":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lava nat a non autoregressive translation model with look around decoding and vocabulary attention")

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)