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: "flexible and creative chinese poetry generation using neural memory"
  Abstract: It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not only rules but also innovations for which pure statistical models are not appropriate in principle. This work proposes a memory-augmented neural model for Chinese poem generation, where the neural model and the augmented memory work together to balance the requirements of linguistic accordance and aesthetic innovation, leading to innovative generations that are still rule-compliant. In addition, it is found that the memory mechanism provides interesting flexibility that can be used to generate poems with different styles.

Connected through hyperedge HE-1 (induced by source paper "mixpoet diverse poetry generation via learning controllable mixed latent space"):
  with members:
    - "cgans with projection discriminator"
    - "spectral normalization for generative adversarial networks"
    - "chinese poetry generation with a working memory model"
    - "toward controlled generation of text"
    - "deep unsupervised clustering with gaussian mixture variational autoencoders"
    - "adversarially regularized autoencoders"
    - "generating thematic chinese poetry using conditional variational autoencoders with hybrid decoders"
    - "learning discourse level diversity for neural dialog models using conditional variational autoencoders"

Connected through hyperedge HE-2 (induced by source paper "review driven answer generation for product related questions in e commerce"):
  with members:
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "modelling domain relationships for transfer learning on retrieval based question answering systems in e commerce"
    - "convolutional sequence to sequence learning"
    - "interactive attention networks for aspect level sentiment classification"
    - "deep reinforcement learning for dialogue generation"
    - "sequence to backward and forward sequences a content introducing approach to generative short text conversation"
    - "how not to evaluate your dialogue system an empirical study of unsupervised evaluation metrics for dialogue response generation"
    - "topic aware neural response generation"

Connected through hyperedge HE-3 (induced by source paper "automatic acrostic couplet generation with three stage neural network pipelines"):
  with members:
    - "weighted transformer network for machine translation"
    - "neural machine translation"
    - "diverse beam search decoding diverse solutions from neural sequence models"
    - "chinese poetry generation with planning based neural network"
    - "a hierarchical recurrent encoder decoder for generative context aware query suggestion"
    - "adam a method for stochastic optimization"
    - "neural machine translation by jointly learning to align and translate"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"

Connected through hyperedge HE-4 (induced by source paper "deep learning and sub word unit approach in written art generation"):
  with members:
    - "image inspired poetry generation in xiaoice"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "guess who multilingual approach for the automated generation of author stylized poetry"
    - "universal language model fine tuning for text classification"
    - "beyond narrative description generating poetry from images by multi adversarial training"
    - "cyclical learning rates for training neural networks"
    - "neural machine translation of rare words with subword units"

Connected through hyperedge HE-5 (induced by source paper "an iterative polishing framework based on quality aware masked language model for chinese poetry generation"):
  with members:
    - "pretraining based natural language generation for text summarization"
    - "chinese poetry generation with a salient clue mechanism"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "chinese poetry generation with a working memory model"
    - "can machine generate traditional chinese poetry a feigenbaum test"
    - "chinese poetry generation with planning based neural network"
    - "towards universal paraphrastic sentence embeddings"

Connected through hyperedge HE-6 (induced by source paper "guess who multilingual approach for the automated generation of author stylized poetry"):
  with members:
    - "what is wrong with style transfer for texts"
    - "delete retrieve generate a simple approach to sentiment and style transfer"
    - "learning to generate reviews and discovering sentiment"
    - "toward controlled generation of text"
    - "generating sentences by editing prototypes"
    - "style transfer from non parallel text by cross alignment"
    - "neural text generation a practical guide"
    - "controlling linguistic style aspects in neural language generation"

Connected through hyperedge HE-7 (induced by source paper "a multi modal chinese poetry generation model"):
  with members:
    - "chinese song iambics generation with neural attention based model"
    - "can machine generate traditional chinese poetry a feigenbaum test"
    - "sequence to backward and forward sequences a content introducing approach to generative short text conversation"
    - "hierarchical question image co attention for visual question answering"
    - "generating chinese classical poems with rnn encoder decoder"
    - "chinese poetry generation with planning based neural network"
    - "a neural attention model for abstractive sentence summarization"
    - "backward and forward language modeling for constrained sentence generation"

Connected through hyperedge HE-8 (induced by source paper "paper abstract writing through editing mechanism"):
  with members:
    - "get to the point summarization with pointer generator networks"
    - "table to text generation by structure aware seq2seq learning"
    - "neural network based abstract generation for opinions and arguments"
    - "incorporating copying mechanism in sequence to sequence learning"
    - "neural text generation from structured data with application to the biography domain"
    - "a theme rewriting approach for generating algebra word problems"
    - "effective approaches to attention based neural machine translation"
    - "neural machine translation by jointly learning to align and translate"

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.AI(Artificial Intelligence)