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 "an operation sequence model for explainable neural machine translation"):
  Abstract: We propose to achieve explainable neural machine translation (NMT) by changing the output representation to explain itself. We present a novel approach to NMT which generates the target sentence by monotonically walking through the source sentence. Word reordering is modeled by operations which allow setting markers in the target sentence and move a target-side write head between those markers. In contrast to many modern neural models, our system emits explicit word alignment information which is often crucial to practical machine translation as it improves explainability. Our technique can outperform a plain text system in terms of BLEU score under the recent Transformer architecture on Japanese-English and Portuguese-English, and is within 0.5 BLEU difference on Spanish-English.

Includes members:
  Member "tensor2tensor for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stress test evaluation of transformer based models in natural language understanding tasks")
  Member "training tips for the transformer model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "disentangling adaptive gradient methods from learning rates")
  Member "neural machine translation decoding with terminology constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "commongen a constrained text generation dataset towards generative commonsense reasoning")
  Member "qcri machine translation systems for iwslt 16":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the impact of preprocessing on arabic english statistical and neural machine translation")
  Member "a causal framework for explaining the predictions of black box sequence to sequence models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "what does attention in neural machine translation pay attention to":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an empirical study of spatial attention mechanisms in deep networks")
  Member "sgnmt a flexible nmt decoding platform for quick prototyping of new models and search strategies":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cued wmt19 ewc lms")

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)