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: "generating chinese classical poems with rnn encoder decoder"
  Abstract: We take the generation of Chinese classical poem lines as a sequence-to-sequence learning problem, and build a novel system based on the RNN Encoder-Decoder structure to generate quatrains (Jueju in Chinese), with a topic word as input. Our system can jointly learn semantic meaning within a single line, semantic relevance among lines in a poem, and the use of structural, rhythmical and tonal patterns, without utilizing any constraint templates. Experimental results show that our system outperforms other competitive systems. We also find that the attention mechanism can capture the word associations in Chinese classical poetry and inverting target lines in training can improve

Connected through hyperedge HE-1 (induced by source paper "creative gans for generating poems lyrics and metaphors"):
  with members:
    - "the curious case of neural text degeneration"
    - "transformer xl attentive language models beyond a fixed length context"
    - "fine tuned language models for text classification"
    - "attention is all you need"
    - "regularizing and optimizing lstm language models"
    - "generating high quality and informative conversation responses with sequence to sequence models"
    - "a deep reinforced model for abstractive summarization"
    - "word ordering without syntax"

Connected through hyperedge HE-2 (induced by source paper "neural poetry learning to generate poems using syllables"):
  with members:
    - "deep speare a joint neural model of poetic language meter and rhyme"
    - "an unsupervised character aware neural approach to word and context representation learning"
    - "adversarial generation of natural language"
    - "chinese song iambics generation with neural attention based model"
    - "seqgan sequence generative adversarial nets with policy gradient"
    - "gated word character recurrent language model"
    - "character level language modeling with hierarchical recurrent neural networks"
    - "neural paraphrase generation with stacked residual lstm networks"

Connected through hyperedge HE-3 (induced by source paper "automatic realistic music video generation from segments of youtube videos"):
  with members:
    - "video generation from text"
    - "transfer learning for music classification and regression tasks"
    - "youtube 8m a large scale video classification benchmark"
    - "deepbach a steerable model for bach chorales generation"
    - "generating videos with scene dynamics"
    - "a neural algorithm of artistic style"

Connected through hyperedge HE-4 (induced by source paper "a syllable structured contextually based conditionally generation of chinese lyrics"):
  with members:
    - "chinese song iambics generation with neural attention based model"
    - "attention based recurrent neural network models for joint intent detection and slot filling"
    - "neural machine translation by jointly learning to align and translate"
    - "sequence to sequence learning with neural networks"

Connected through hyperedge HE-5 (induced by source paper "deep poetry a chinese classical poetry generation system"):
  with members:
    - "a multi modal chinese poetry generation model"
    - "chinese song iambics generation with neural attention based model"

Connected through hyperedge HE-6 (induced by source paper "a multi modal chinese poetry generation model"):
  with members:
    - "flexible and creative chinese poetry generation using neural memory"
    - "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"
    - "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-7 (induced by source paper "beyond narrative description generating poetry from images by multi adversarial training"):
  with members:
    - "how images inspire poems generating classical chinese poetry from images with memory networks"
    - "show adapt and tell adversarial training of cross domain image captioner"
    - "seqgan sequence generative adversarial nets with policy gradient"
    - "image captioning with semantic attention"
    - "boosting image captioning with attributes"
    - "a hierarchical approach for generating descriptive image paragraphs"
    - "self critical sequence training for image captioning"
    - "skip thought vectors"

Connected through hyperedge HE-8 (induced by source paper "image inspired poetry generation in xiaoice"):
  with members:
    - "from eliza to xiaoice challenges and opportunities with social chatbots"
    - "chinese song iambics generation with neural attention based model"
    - "how not to evaluate your dialogue system an empirical study of unsupervised evaluation metrics for dialogue response generation"
    - "automatic description generation from images a survey of models datasets and evaluation measures"
    - "chinese poetry generation with planning based neural network"
    - "language models for image captioning the quirks and what works"
    - "microsoft coco captions data collection and evaluation server"
    - "adam a method for stochastic optimization"

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.CL(Computation and Language)