human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "tensor2tensor for neural machine translation"
  Abstract: Tensor2Tensor is a library for deep learning models that is well-suited for neural machine translation and includes the reference implementation of the state-of-the-art Transformer model.

Connected through hyperedge HE-1 (induced by source paper "stress test evaluation of transformer based models in natural language understanding tasks"):
  with members:
    - "huggingface s transformers state of the art natural language processing"
    - "universal transformers"
    - "a multiscale visualization of attention in the transformer model"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "probing neural network comprehension of natural language arguments"
    - "roberta a robustly optimized bert pretraining approach"
    - "is bert really robust a strong baseline for natural language attack on text classification and entailment"
    - "on adversarial examples for character level neural machine translation"

Connected through hyperedge HE-2 (induced by source paper "bertscore evaluating text generation with bert"):
  with members:
    - "fairseq a fast extensible toolkit for sequence modeling"
    - "fine tune bert for extractive summarization"
    - "alternative weighting schemes for elmo embeddings"
    - "deep reinforcement learning with distributional semantic rewards for abstractive summarization"
    - "pay less attention with lightweight and dynamic convolutions"
    - "simple applications of bert for ad hoc document retrieval"
    - "unifying human and statistical evaluation for natural language generation"
    - "scibert a pretrained language model for scientific text"

Connected through hyperedge HE-3 (induced by source paper "consistency by agreement in zero shot neural machine translation"):
  with members:
    - "the missing ingredient in zero shot neural machine translation"
    - "xnli evaluating cross lingual sentence representations"
    - "style transfer through back translation"
    - "large scale distributed neural network training through online distillation"
    - "a neural interlingua for multilingual machine translation"
    - "contextual parameter generation for universal neural machine translation"
    - "phrase based neural unsupervised machine translation"
    - "zero shot dual machine translation"

Connected through hyperedge HE-4 (induced by source paper "neural shuffle exchange networks sequence processing in o n log n time"):
  with members:
    - "transformer xl attentive language models beyond a fixed length context"
    - "star transformer"
    - "universal transformers"
    - "generating long sequences with sparse transformers"
    - "recent advances in neural program synthesis"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "character level language modeling with deeper self attention"
    - "music transformer"

Connected through hyperedge HE-5 (induced by source paper "a learned representation for scalable vector graphics"):
  with members:
    - "figr few shot image generation with reptile"
    - "large scale gan training for high fidelity natural image synthesis"
    - "a style based generator architecture for generative adversarial networks"
    - "synthesizing programs for images using reinforced adversarial learning"
    - "attention is all you need"
    - "film visual reasoning with a general conditioning layer"
    - "learning to infer graphics programs from hand drawn images"
    - "a neural representation of sketch drawings"

Connected through hyperedge HE-6 (induced by source paper "self attentional models application in task oriented dialogue generation systems"):
  with members:
    - "universal transformers"
    - "generating wikipedia by summarizing long sequences"
    - "building a conversational agent overnight with dialogue self play"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "conversational ai the science behind the alexa prize"
    - "key value retrieval networks for task oriented dialogue"
    - "attention is all you need"
    - "a survey on dialogue systems recent advances and new frontiers"

Connected through hyperedge HE-7 (induced by source paper "videoflow a flow based generative model for video"):
  with members:
    - "stochastic adversarial video prediction"
    - "stochastic video generation with a learned prior"
    - "fast generation for convolutional autoregressive models"
    - "self supervised visual planning with temporal skip connections"
    - "the reversible residual network backpropagation without storing activations"
    - "attention is all you need"
    - "stochastic variational video prediction"
    - "parallel multiscale autoregressive density estimation"

Connected through hyperedge HE-8 (induced by source paper "fast structured decoding for sequence models"):
  with members:
    - "non autoregressive machine translation with auxiliary regularization"
    - "hint based training for non autoregressive machine translation"
    - "a tutorial on deep latent variable models of natural language"
    - "deterministic non autoregressive neural sequence modeling by iterative refinement"
    - "fast decoding in sequence models using discrete latent variables"
    - "non autoregressive neural machine translation with enhanced decoder input"
    - "theory and experiments on vector quantized autoencoders"
    - "end to end non autoregressive neural machine translation with connectionist temporal classification"

Question: Please tell me which class the center node 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.LG(Machine Learning)