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: "transferable multi domain state generator for task oriented dialogue systems"
  Abstract: Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking. Existing approaches generally fall short in tracking unknown slot values during inference and often have difficulties in adapting to new domains. In this paper, we propose a Transferable Dialogue State Generator (TRADE) that generates dialogue states from utterances using a copy mechanism, facilitating knowledge transfer when predicting (domain, slot, value) triplets not encountered during training. Our model is composed of an utterance encoder, a slot gate, and a state generator, which are shared across domains. Empirical results demonstrate that TRADE achieves state-of-the-art joint goal accuracy of 48.62% for the five domains of MultiWOZ, a human-human dialogue dataset. In addition, we show its transferring ability by simulating zero-shot and few-shot dialogue state tracking for unseen domains. TRADE achieves 60.58% joint goal accuracy in one of the zero-shot domains, and is able to adapt to few-shot cases without forgetting already trained domains.

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"
    - "importance of search and evaluation strategies in neural dialogue modeling"

Connected through hyperedge HE-3 (induced by source paper "variational hierarchical dialog autoencoder for dialogue state tracking data augmentation"):
  with members:
    - "lagging inference networks and posterior collapse in variational autoencoders"
    - "eda easy data augmentation techniques for boosting performance on text classification tasks"
    - "dialog state tracking with reinforced data augmentation"
    - "dialogwae multimodal response generation with conditional wasserstein auto encoder"
    - "user modeling for task oriented dialogues"
    - "data augmentation for spoken language understanding via joint variational generation"
    - "a hierarchical latent structure for variational conversation modeling"
    - "isolating sources of disentanglement in variational autoencoders"

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"
    - "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"
    - "neural approaches to conversational ai"

Connected through hyperedge HE-5 (induced by source paper "non autoregressive dialog state tracking"):
  with members:
    - "non autoregressive machine translation with auxiliary regularization"
    - "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"
    - "sumbt slot utterance matching for universal and scalable belief tracking"
    - "deterministic non autoregressive neural sequence modeling by iterative refinement"
    - "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling"
    - "toward scalable neural dialogue state tracking model"

Connected through hyperedge HE-6 (induced by source paper "convlab 2 an open source toolkit for building evaluating and diagnosing dialogue systems"):
  with members:
    - "plato dialogue system a flexible conversational ai research platform"
    - "crosswoz a large scale chinese cross domain task oriented dialogue dataset"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "sumbt slot utterance matching for universal and scalable belief tracking"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "convlab multi domain end to end dialog system platform"
    - "rethinking action spaces for reinforcement learning in end to end dialog agents with latent variable models"
    - "guided dialog policy learning reward estimation for multi domain task oriented dialog"

Connected through hyperedge HE-7 (induced by source paper "schema guided dialogue state tracking task at dstc8"):
  with members:
    - "fine tuning bert for schema guided zero shot dialogue state tracking"
    - "goal oriented multi task bert based dialogue state tracker"
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "robust zero shot cross domain slot filling with example values"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "an end to end dialogue state tracking system with machine reading comprehension and wide deep classification"

Connected through hyperedge HE-8 (induced by source paper "goal oriented multi task bert based dialogue state tracker"):
  with members:
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "bert dst scalable end to end dialogue state tracking with bidirectional encoder representations from transformer"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "towards universal dialogue state tracking"
    - "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"

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)