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: "dialog state tracking a machine reading approach using memory network"
  Abstract: In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate a compact representation of the current dialog status from a sequence of noisy observations produced by the speech recognition and the natural language understanding modules. This paper introduces a novel method of dialog state tracking based on the general paradigm of machine reading and proposes to solve it using an End-to-End Memory Network, MemN2N, a memory-enhanced neural network architecture. We evaluate the proposed approach on the second Dialog State Tracking Challenge (DSTC-2) dataset. The corpus has been converted for the occasion in order to frame the hidden state variable inference as a question-answering task based on a sequence of utterances extracted from a dialog. We show that the proposed tracker gives encouraging results. Then, we propose to extend the DSTC-2 dataset with specific reasoning capabilities requirement like counting, list maintenance, yes-no question answering and indefinite knowledge management. Finally, we present encouraging results using our proposed MemN2N based tracking model.

Connected through hyperedge HE-1 (induced by source paper "procedural reasoning networks for understanding multimodal procedures"):
  with members:
    - "be consistent improving procedural text comprehension using label consistency"
    - "the natural language decathlon multitask learning as question answering"
    - "recipe1m a dataset for learning cross modal embeddings for cooking recipes and food images"
    - "building dynamic knowledge graphs from text using machine reading comprehension"
    - "neural models for reasoning over multiple mentions using coreference"
    - "relational recurrent neural networks"
    - "tracking state changes in procedural text a challenge dataset and models for process paragraph comprehension"
    - "allennlp a deep semantic natural language processing platform"

Connected through hyperedge HE-2 (induced by source paper "scalable and accurate dialogue state tracking via hierarchical sequence generation"):
  with members:
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "dialog state tracking a neural reading comprehension approach"
    - "on the convergence of adam and beyond"
    - "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"
    - "sgm sequence generation model for multi label classification"
    - "global locally self attentive dialogue state tracker"

Connected through hyperedge HE-3 (induced by source paper "dialog state tracking a neural reading comprehension approach"):
  with members:
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "linguistic knowledge and transferability of contextual representations"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "sdnet contextualized attention based deep network for conversational question answering"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "global locally self attentive dialogue state tracker"
    - "deep contextualized word representations"
    - "coqa a conversational question answering challenge"

Connected through hyperedge HE-4 (induced by source paper "an end to end dialogue state tracking system with machine reading comprehension and wide deep classification"):
  with members:
    - "dialog state tracking a neural reading comprehension approach"
    - "bert dst scalable end to end dialogue state tracking with bidirectional encoder representations from transformer"
    - "find or classify dual strategy for slot value predictions on multi domain dialog state tracking"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "roberta a robustly optimized bert pretraining approach"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"

Connected through hyperedge HE-5 (induced by source paper "multi domain dialogue state tracking as dynamic knowledge graph enhanced question answering"):
  with members:
    - "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"
    - "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"
    - "kg 2 learning to reason science exam questions with contextual knowledge graph embeddings"
    - "allennlp a deep semantic natural language processing platform"

Connected through hyperedge HE-6 (induced by source paper "hyst a hybrid approach for flexible and accurate dialogue state tracking"):
  with members:
    - "towards universal dialogue state tracking"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "global locally self attentive dialogue state tracker"
    - "multi task learning for joint language understanding and dialogue state tracking"
    - "flexible and scalable state tracking framework for goal oriented dialogue systems"
    - "multiwoz a large scale multi domain wizard of oz dataset for task oriented dialogue modelling"
    - "toward scalable neural dialogue state tracking model"
    - "scalable multi domain dialogue state tracking"

Connected through hyperedge HE-7 (induced by source paper "copy enhanced heterogeneous information learning for dialogue state tracking"):
  with members:
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "scalable multi domain dialogue state tracking"
    - "a network based end to end trainable task oriented dialogue system"
    - "towards end to end reinforcement learning of dialogue agents for information access"
    - "a joint many task model growing a neural network for multiple nlp tasks"
    - "neural belief tracker data driven dialogue state tracking"
    - "learning end to end goal oriented dialog"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-8 (induced by source paper "explicit state tracking with semi supervisionfor neural dialogue generation"):
  with members:
    - "prior knowledge integration for neural machine translation using posterior regularization"
    - "key value retrieval networks for task oriented dialogue"
    - "latent variable dialogue models and their diversity"
    - "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning"
    - "a persona based neural conversation model"
    - "a network based end to end trainable task oriented dialogue system"
    - "how not to evaluate your dialogue system an empirical study of unsupervised evaluation metrics for dialogue response generation"
    - "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)