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: "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning"
  Abstract: End-to-end learning of recurrent neural networks (RNNs) is an attractive solution for dialog systems; however, current techniques are data-intensive and require thousands of dialogs to learn simple behaviors. We introduce Hybrid Code Networks (HCNs), which combine an RNN with domain-specific knowledge encoded as software and system action templates. Compared to existing end-to-end approaches, HCNs considerably reduce the amount of training data required, while retaining the key benefit of inferring a latent representation of dialog state. In addition, HCNs can be optimized with supervised learning, reinforcement learning, or a mixture of both. HCNs attain state-of-the-art performance on the bAbI dialog dataset, and outperform two commercially deployed customer-facing dialog systems.

Connected through hyperedge HE-1 (induced by source paper "recent advances and challenges in task oriented dialog system"):
  with members:
    - "convlab 2 an open source toolkit for building evaluating and diagnosing dialogue systems"
    - "crosswoz a large scale chinese cross domain task oriented dialogue dataset"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "global to local memory pointer networks for task oriented dialogue"
    - "domain adaptive dialog generation via meta learning"
    - "meta learning for low resource natural language generation in task oriented dialogue systems"
    - "unsupervised dialog structure learning"
    - "cosql a conversational text to sql challenge towards cross domain natural language interfaces to databases"

Connected through hyperedge HE-2 (induced by source paper "attention over parameters for dialogue systems"):
  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"
    - "moel mixture of empathetic listeners"
    - "deepcopy grounded response generation with hierarchical pointer networks"
    - "caire an end to end empathetic chatbot"
    - "learning from dialogue after deployment feed yourself chatbot"
    - "transferable multi domain state generator for task oriented dialogue systems"

Connected through hyperedge HE-3 (induced by source paper "if i hear you correctly building and evaluating interview chatbots with active listening skills"):
  with members:
    - "tell me about yourself using an ai powered chatbot to conduct conversational surveys"
    - "universal sentence encoder"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "joint embedding of words and labels for text classification"
    - "touch your heart a tone aware chatbot for customer care on social media"
    - "emotional chatting machine emotional conversation generation with internal and external memory"
    - "learning to ask neural question generation for reading comprehension"
    - "learning conversational systems that interleave task and non task content"

Connected through hyperedge HE-4 (induced by source paper "crwiz a framework for crowdsourcing real time wizard of oz dialogues"):
  with members:
    - "natural language interaction to facilitate mental models of remote robots"
    - "meetup a corpus of joint activity dialogues in a visual environment"
    - "persuasion for good towards a personalized persuasive dialogue system for social good"
    - "end to end trainable non collaborative dialog system"
    - "the orca hub explainable offshore robotics through intelligent interfaces"
    - "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling"
    - "learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings"
    - "frames a corpus for adding memory to goal oriented dialogue systems"

Connected through hyperedge HE-5 (induced by source paper "multipurpose intelligent process automation via conversational assistant"):
  with members:
    - "global to local memory pointer networks for task oriented dialogue"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "limits of end to end learning"
    - "a survey on dialogue systems recent advances and new frontiers"
    - "rasa open source language understanding and dialogue management"
    - "a network based end to end trainable task oriented dialogue system"

Connected through hyperedge HE-6 (induced by source paper "learning to memorize in neural task oriented dialogue systems"):
  with members:
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "zero shot dialog generation with cross domain latent actions"
    - "skeleton to response dialogue generation guided by retrieval memory"
    - "the natural language decathlon multitask learning as question answering"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "emo2vec learning generalized emotion representation by multi task training"
    - "global locally self attentive dialogue state tracker"

Connected through hyperedge HE-7 (induced by source paper "self supervised dialogue learning"):
  with members:
    - "multi task deep neural networks for natural language understanding"
    - "self supervised learning for contextualized extractive summarization"
    - "cross lingual language model pretraining"
    - "adversarial learning of task oriented neural dialog models"
    - "deep dyna q integrating planning for task completion dialogue policy learning"
    - "deep contextualized word representations"
    - "neural approaches to conversational ai"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-8 (induced by source paper "macnet transferring knowledge from machine comprehension to sequence to sequence models"):
  with members:
    - "discourse marker augmented network with reinforcement learning for natural language inference"
    - "soft layer specific multi task summarization with entailment and question generation"
    - "selective encoding for abstractive sentence summarization"
    - "reinforced mnemonic reader for machine comprehension"
    - "memen multi layer embedding with memory networks for machine comprehension"
    - "focal loss for dense object detection"
    - "triviaqa a large scale distantly supervised challenge dataset for reading comprehension"
    - "attention over attention neural networks for reading comprehension"

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)