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 network based end to end trainable task oriented dialogue system"
  Abstract: Teaching machines to accomplish tasks by conversing naturally with humans is challenging. Currently, developing task-oriented dialogue systems requires creating multiple components and typically this involves either a large amount of handcrafting, or acquiring costly labelled datasets to solve a statistical learning problem for each component. In this work we introduce a neural network-based text-in, text-out end-to-end trainable goal-oriented dialogue system along with a new way of collecting dialogue data based on a novel pipe-lined Wizard-of-Oz framework. This approach allows us to develop dialogue systems easily and without making too many assumptions about the task at hand. The results show that the model can converse with human subjects naturally whilst helping them to accomplish tasks in a restaurant search domain.

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 "efficient intent detection with dual sentence encoders"):
  with members:
    - "q8bert quantized 8bit bert"
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "training neural response selection for task oriented dialogue systems"
    - "pretraining methods for dialog context representation learning"
    - "to tune or not to tune adapting pretrained representations to diverse tasks"
    - "a repository of conversational datasets"
    - "zero shot cross lingual dialogue systems with transferable latent variables"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"

Connected through hyperedge HE-4 (induced by source paper "ma dst multi attention based scalable dialog state tracking"):
  with members:
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "dialog state tracking a neural reading comprehension approach"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "roberta a robustly optimized bert pretraining approach"
    - "sdnet contextualized attention based deep network for conversational question answering"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "deep contextualized word representations"

Connected through hyperedge HE-5 (induced by source paper "few shot natural language generation for task oriented dialog"):
  with members:
    - "towards a human like open domain chatbot"
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "plug and play language models a simple approach to controlled text generation"
    - "ctrl a conditional transformer language model for controllable generation"
    - "defending against neural fake news"
    - "semantically conditioned dialog response generation via hierarchical disentangled self attention"
    - "dialogpt large scale generative pre training for conversational response generation"
    - "xlnet generalized autoregressive pretraining for language understanding"

Connected through hyperedge HE-6 (induced by source paper "hierarchical context enhanced multi domain dialogue system for multi domain task completion"):
  with members:
    - "structured fusion networks for dialog"
    - "convlab multi domain end to end dialog system platform"
    - "onenet joint domain intent slot prediction for spoken language understanding"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling"
    - "large scale multi domain belief tracking with knowledge sharing"
    - "scalable multi domain dialogue state tracking"
    - "composite task completion dialogue policy learning via hierarchical deep reinforcement learning"

Connected through hyperedge HE-7 (induced by source paper "crosswoz a large scale chinese cross domain task oriented dialogue dataset"):
  with members:
    - "convlab 2 an open source toolkit for building evaluating and diagnosing dialogue systems"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "guided dialog policy learning reward estimation for multi domain task oriented dialog"
    - "pre training with whole word masking for chinese bert"
    - "building a conversational agent overnight with dialogue self play"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "key value retrieval networks for task oriented dialogue"

Connected through hyperedge HE-8 (induced by source paper "data augmentation for copy mechanism in dialogue state tracking"):
  with members:
    - "scalable and accurate dialogue state tracking via hierarchical sequence generation"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling"
    - "large scale multi domain belief tracking with knowledge sharing"
    - "get to the point summarization with pointer generator networks"
    - "incorporating copying mechanism in sequence to sequence learning"

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)