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: "a survey of available corpora for building data driven dialogue systems"
  Abstract: During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge. Nevertheless, several recent results suggest that data-driven approaches are feasible and quite promising. To facilitate research in this area, we have carried out a wide survey of publicly available datasets suitable for data-driven learning of dialogue systems. We discuss important characteristics of these datasets and how they can be used to learn diverse dialogue strategies. We also describe other potential uses of these datasets, such as methods for transfer learning between datasets and the use of external knowledge, and discuss appropriate choice of evaluation metrics for the learning objective.

Connected through hyperedge HE-1 (induced by source paper "the apiza corpus api usage dialogues with a simulated virtual assistant"):
  with members:
    - "detecting speech act types in developer question answer conversations during bug repair"

Connected through hyperedge HE-2 (induced by source paper "survey on evaluation methods for dialogue systems"):
  with members:
    - "learning from dialogue after deployment feed yourself chatbot"
    - "the design and implementation of xiaoice an empathetic social chatbot"
    - "dialogue learning with human teaching and feedback in end to end trainable task oriented dialogue systems"
    - "coqa a conversational question answering challenge"
    - "topic based evaluation for conversational bots"
    - "neural user simulation for corpus based policy optimisation for spoken dialogue systems"
    - "quac question answering in context"
    - "a hybrid convolutional variational autoencoder for text generation"

Connected through hyperedge HE-3 (induced by source paper "getting to know you user attribute extraction from dialogues"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "global to local memory pointer networks for task oriented dialogue"
    - "deepcopy grounded response generation with hierarchical pointer networks"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "aiming to know you better perhaps makes me a more engaging dialogue partner"
    - "retrieve and refine improved sequence generation models for dialogue"
    - "training millions of personalized dialogue agents"

Connected through hyperedge HE-4 (induced by source paper "learning from dialogue after deployment feed yourself chatbot"):
  with members:
    - "beyond turing intelligent agents centered on the user"
    - "bootstrapping conversational agents with weak supervision"
    - "training millions of personalized dialogue agents"
    - "dialogue learning with human teaching and feedback in end to end trainable task oriented dialogue systems"
    - "a hierarchical multi task approach for learning embeddings from semantic tasks"
    - "learning to ask good questions ranking clarification questions using neural expected value of perfect information"
    - "interactive language acquisition with one shot visual concept learning through a conversational game"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-5 (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"
    - "assigning personality identity to a chatting machine for coherent conversation generation"
    - "low rank rnn adaptation for context aware language modeling"

Connected through hyperedge HE-6 (induced by source paper "lifelong and interactive learning of factual knowledge in dialogues"):
  with members:
    - "towards an engine for lifelong interactive knowledge learning in human machine conversations"
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "listen interact and talk learning to speak via interaction"
    - "towards a continuous knowledge learning engine for chatbots"
    - "one shot relational learning for knowledge graphs"
    - "response ranking with deep matching networks and external knowledge in information seeking conversation systems"
    - "naturalizing a programming language via interactive learning"
    - "adversarial learning for neural dialogue generation"

Connected through hyperedge HE-7 (induced by source paper "multilingual dialogue generation with shared private memory"):
  with members:
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "attention is all you need"
    - "dailydialog a manually labelled multi turn dialogue dataset"
    - "a survey on dialogue systems recent advances and new frontiers"
    - "adversarial multi task learning for text classification"
    - "an overview of multi task learning in deep neural networks"
    - "one model to learn them all"
    - "key value memory networks for directly reading documents"

Connected through hyperedge HE-8 (induced by source paper "taskmaster 1 toward a realistic and diverse dialog dataset"):
  with members:
    - "fairseq a fast extensible toolkit for sequence modeling"
    - "towards exploiting background knowledge for building conversation systems"
    - "attention is all you need"
    - "edina building an open domain socialbot with self dialogues"
    - "convolutional sequence to sequence learning"
    - "incorporating copying mechanism in sequence to sequence learning"
    - "wavenet a generative model for raw audio"
    - "learning end to end goal oriented dialog"

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)