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 different story tellings from semantic representations of narrative"
  Abstract: In order to tell stories in different voices for different audiences, interactive story systems require: (1) a semantic representation of story structure, and (2) the ability to automatically generate story and dialogue from this semantic representation using some form of Natural Language Generation (nlg). However, there has been limited research on methods for linking story structures to narrative descriptions of scenes and story events. In this paper we present an automatic method for converting from Scheherazade's story intention graph, a semantic representation, to the input required by the personage nlg engine. Using 36 Aesop Fables distributed in DramaBank, a collection of story encodings, we train translation rules on one story and then test these rules by generating text for the remaining 35. The results are measured in terms of the string similarity metrics Levenshtein Distance and BLEU score. The results show that we can generate the 35 stories with correct content: the test set stories on average are close to the output of the Scheherazade realizer, which was customized to this semantic representation. We provide some examples of story variations generated by personage. In future work, we will experiment with measuring the quality of the same stories generated in different voices, and with techniques for making storytelling interactive.

Connected through hyperedge HE-1 (induced by source paper "my way of telling a story persona based grounded story generation"):
  with members:
    - "contextualize show and tell a neural visual storyteller"
    - "a pipeline for creative visual storytelling"
    - "delete retrieve generate a simple approach to sentiment and style transfer"
    - "story ending generation with incremental encoding and commonsense knowledge"
    - "style transfer through back translation"
    - "content preserving text generation with attribute controls"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "glac net glocal attention cascading networks for multi image cued story generation"

Connected through hyperedge HE-2 (induced by source paper "induction and reference of entities in a visual story"):
  with members:
    - "strategies for structuring story generation"
    - "contextualize show and tell a neural visual storyteller"
    - "a pipeline for creative visual storytelling"
    - "a skeleton based model for promoting coherence among sentences in narrative story generation"
    - "plan and write towards better automatic storytelling"
    - "glac net glocal attention cascading networks for multi image cued story generation"
    - "hierarchical neural story generation"
    - "using inter sentence diverse beam search to reduce redundancy in visual storytelling"

Connected through hyperedge HE-3 (induced by source paper "plan and write towards better automatic storytelling"):
  with members:
    - "story ending generation with incremental encoding and commonsense knowledge"
    - "a skeleton based model for promoting coherence among sentences in narrative story generation"
    - "no metrics are perfect adversarial reward learning for visual storytelling"
    - "hierarchical neural story generation"
    - "event representations for automated story generation with deep neural nets"
    - "regularizing and optimizing lstm language models"
    - "story generation from sequence of independent short descriptions"
    - "m2d monolog to dialog generation for conversational story telling"

Connected through hyperedge HE-4 (induced by source paper "generating sentence planning variations for story telling"):
  with members:
    - "narrative variations in a virtual storyteller"
    - "individual and domain adaptation in sentence planning for dialogue"
    - "a flexible pragmatics driven language generator for animated agents"

Connected through hyperedge HE-5 (induced by source paper "personabank a corpus of personal narratives and their story intention graphs"):
  with members:
    - "narrative variations in a virtual storyteller"
    - "generating sentence planning variations for story telling"

Connected through hyperedge HE-6 (induced by source paper "m2d monolog to dialog generation for conversational story telling"):
  with members:
    - "personabank a corpus of personal narratives and their story intention graphs"
    - "generating sentence planning variations for story telling"

Connected through hyperedge HE-7 (induced by source paper "narrative variations in a virtual storyteller"):
  with members:
    - "automating direct speech variations in stories and games"

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)