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: "assigning personality identity to a chatting machine for coherent conversation generation"
  Abstract: Endowing a chatbot with personality or an identity is quite challenging but critical to deliver more realistic and natural conversations. In this paper, we address the issue of generating responses that are coherent to a pre-specified agent profile. We design a model consisting of three modules: a profile detector to decide whether a post should be responded using the profile and which key should be addressed, a bidirectional decoder to generate responses forward and backward starting from a selected profile value, and a position detector that predicts a word position from which decoding should start given a selected profile value. We show that general conversation data from social media can be used to generate profile-coherent responses. Manual and automatic evaluation shows that our model can deliver more coherent, natural, and diversified responses.

Connected through hyperedge HE-1 (induced by source paper "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "personalized dialogue generation with diversified traits"
    - "learning to write with cooperative discriminators"
    - "training millions of personalized dialogue agents"
    - "towards empathetic open domain conversation models a new benchmark and dataset"
    - "wizard of wikipedia knowledge powered conversational agents"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "polite dialogue generation without parallel data"

Connected through hyperedge HE-2 (induced by source paper "c textgen conditional text generation for harmonious human machine interaction"):
  with members:
    - "towards knowledge based personalized product description generation in e commerce"
    - "improving neural response diversity with frequency aware cross entropy loss"
    - "an adversarial approach to high quality sentiment controlled neural dialogue generation"
    - "topic guided variational autoencoders for text generation"
    - "knowledge aware conversation generation with explainable reasoning on augmented graphs"
    - "knowledge aware conversation generation with reasoning on augmented graph"
    - "reinforcement learning based emotional editing constraint conversation generation"
    - "towards an engine for lifelong interactive knowledge learning in human machine conversations"

Connected through hyperedge HE-3 (induced by source paper "ai powered text generation for harmonious human machine interaction current state and future directions"):
  with members:
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "learning personalized end to end goal oriented dialog"
    - "multi reward reinforced summarization with saliency and entailment"
    - "learning to generate reviews and discovering sentiment"
    - "key value retrieval networks for task oriented dialogue"
    - "survey of the state of the art in natural language generation core tasks applications and evaluation"
    - "automatic generation of natural language explanations"
    - "improving context aware language models"

Connected through hyperedge HE-4 (induced by source paper "consistent dialogue generation with self supervised feature learning"):
  with members:
    - "jointly optimizing diversity and relevance in neural response generation"
    - "unsupervised discrete sentence representation learning for interpretable neural dialog generation"
    - "nash toward end to end neural architecture for generative semantic hashing"
    - "dialogue natural language inference"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "neural approaches to conversational ai"
    - "generating informative and diverse conversational responses via adversarial information maximization"
    - "audio visual scene analysis with self supervised multisensory features"

Connected through hyperedge HE-5 (induced by source paper "sketch fill a r a persona grounded chit chat generation framework"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "global to local memory pointer networks for task oriented dialogue"
    - "importance of search and evaluation strategies in neural dialogue modeling"
    - "the design and implementation of xiaoice an empathetic social chatbot"
    - "dialogue natural language inference"
    - "wizard of wikipedia knowledge powered conversational agents"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "importance of a search strategy in neural dialogue modelling"

Connected through hyperedge HE-6 (induced by source paper "personalized dialogue generation with diversified traits"):
  with members:
    - "training millions of personalized dialogue agents"
    - "from eliza to xiaoice challenges and opportunities with social chatbots"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "a systematic study of the class imbalance problem in convolutional neural networks"
    - "emotional chatting machine emotional conversation generation with internal and external memory"
    - "addressee and response selection in multi party conversations with speaker interaction rnns"
    - "low rank rnn adaptation for context aware language modeling"
    - "personalization in goal oriented dialog"

Connected through hyperedge HE-7 (induced by source paper "gsn a graph structured network for multi party dialogues"):
  with members:
    - "graph to sequence learning using gated graph neural networks"
    - "addressee and response selection in multi party conversations with speaker interaction rnns"
    - "emergence of language with multi agent games learning to communicate with sequences of symbols"
    - "dynamic routing between capsules"
    - "towards neural speaker modeling in multi party conversation the task dataset and models"
    - "encoding sentences with graph convolutional networks for semantic role labeling"
    - "a persona based neural conversation model"
    - "lstm based conversation models"

Connected through hyperedge HE-8 (induced by source paper "a pre training based personalized dialogue generation model with persona sparse data"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "pretraining methods for dialog context representation learning"
    - "ernie enhanced representation through knowledge integration"
    - "exploiting persona information for diverse generation of conversational responses"
    - "challenges in building intelligent open domain dialog systems"
    - "sentilr linguistic knowledge enhanced language representation for sentiment analysis"
    - "hello it s gpt 2 how can i help you towards the use of pretrained language models for task oriented dialogue systems"

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)