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: "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
  Abstract: MultiWOZ is a recently-released multidomain dialogue dataset spanning 7 distinct domains and containing over 10000 dialogues, one of the largest resources of its kind to-date. Though an immensely useful resource, while building different classes of dialogue state tracking models using MultiWOZ, we detected substantial errors in the state annotations and dialogue utterances which negatively impacted the performance of our models. In order to alleviate this problem, we use crowdsourced workers to fix the state annotations and utterances in the original version of the data. Our correction process results in changes to over 32% of state annotations across 40% of the dialogue turns. In addition, we fix 146 dialogue utterances throughout the dataset focusing in particular on addressing slot value errors represented within the conversations. We then benchmark a number of state-of-the-art dialogue state tracking models on this new MultiWOZ 2.1 dataset and show joint state tracking performance on the corrected state annotations. We are publicly releasing MultiWOZ 2.1 to the community, hoping that this dataset resource will allow for more effective dialogue state tracking models to be built in the future.

Connected through hyperedge HE-1 (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"
    - "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"
    - "neural approaches to conversational ai"

Connected through hyperedge HE-2 (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"
    - "sumbt slot utterance matching for universal and scalable belief tracking"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "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-3 (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"
    - "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"
    - "semantically conditioned dialog response generation via hierarchical disentangled self attention"

Connected through hyperedge HE-4 (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"
    - "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"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "an end to end dialogue state tracking system with machine reading comprehension and wide deep classification"

Connected through hyperedge HE-5 (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"
    - "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"
    - "composite task completion dialogue policy learning via hierarchical deep reinforcement learning"

Connected through hyperedge HE-6 (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"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "convert efficient and accurate conversational representations from transformers"):
  with members:
    - "deep retrieval based dialogue systems a short review"
    - "q8bert quantized 8bit bert"
    - "designing for health chatbots"
    - "are sixteen heads really better than one"
    - "dialog system technology challenge 7"
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "extreme language model compression with optimal subwords and shared projections"
    - "dialogue transformers"

Connected through hyperedge HE-8 (induced by source paper "towards scalable multi domain conversational agents the schema guided dialogue dataset"):
  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"
    - "robust zero shot cross domain slot filling with example values"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "towards universal dialogue state tracking"
    - "building a conversational agent overnight with dialogue self play"
    - "multi task learning for joint language understanding and dialogue state tracking"
    - "deep contextualized word representations"

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)