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: "just ask building an architecture for extensible self service spoken language understanding"
  Abstract: This paper presents the design of the machine learning architecture that underlies the Alexa Skills Kit (ASK), which was the first Spoken Language Understanding (SLU) Software Development Kit (SDK) for a virtual digital assistant, as far as we are aware. At Amazon, the infrastructure powers more than 20,000 skills built through the ASK, as well as AWS's Amazon Lex SLU Service. The ASK emphasizes flexibility, predictability and a rapid iteration cycle for third party developers. It imposes inductive biases that allow it to learn robust SLU models from extremely small and sparse datasets and, in doing so, removes significant barriers to entry for software developers and dialog systems researchers.

Connected through hyperedge HE-1 (induced by source paper "schema2qa answering complex queries on the structured web with a neural model"):
  with members:
    - "genie a generator of natural language semantic parsers for virtual assistant commands"
    - "a comprehensive exploration on wikisql with table aware word contextualization"
    - "towards complex text to sql in cross domain database with intermediate representation"
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "sqlnet generating structured queries from natural language without reinforcement learning"
    - "the natural language decathlon multitask learning as question answering"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "tranx a transition based neural abstract syntax parser for semantic parsing and code generation"

Connected through hyperedge HE-2 (induced by source paper "pseudo labeling and negative feedback learning for large scale multi label domain classification"):
  with members:
    - "learning from dialogue after deployment feed yourself chatbot"
    - "a scalable neural shortlisting reranking approach for large scale domain classification in natural language understanding"
    - "efficient large scale domain classification with personalized attention"
    - "strong baselines for neural semi supervised learning under domain shift"
    - "classification from positive unlabeled and biased negative data"
    - "supervised domain enablement attention for personalized domain classification"
    - "mean teachers are better role models weight averaged consistency targets improve semi supervised deep learning results"
    - "a structured self attentive sentence embedding"

Connected through hyperedge HE-3 (induced by source paper "towards personalized dialog policies for conversational skill discovery"):
  with members:
    - "the technological gap between virtual assistants and recommendation systems"
    - "continuous learning for large scale personalized domain classification"
    - "efficient large scale domain classification with personalized attention"
    - "dialogue learning with human teaching and feedback in end to end trainable task oriented dialogue systems"
    - "attentive memory networks efficient machine reading for conversational search"
    - "learning robust dialog policies in noisy environments"
    - "improving search through a3c reinforcement learning based conversational agent"
    - "simpleds a simple deep reinforcement learning dialogue system"

Connected through hyperedge HE-4 (induced by source paper "scaling multi domain dialogue state tracking via query reformulation"):
  with members:
    - "a dataset for resolving referring expressions in spoken dialogue via contextual query rewrites cqr"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "contextual slot carryover for disparate schemas"
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "key value retrieval networks for task oriented dialogue"
    - "scalable multi domain dialogue state tracking"
    - "opennmt open source toolkit for neural machine translation"
    - "get to the point summarization with pointer generator networks"

Connected through hyperedge HE-5 (induced by source paper "investigation of error simulation techniques for learning dialog policies for conversational error recovery"):
  with members:
    - "closing the sim to real loop adapting simulation randomization with real world experience"
    - "learning robust dialog policies in noisy environments"
    - "end to end task completion neural dialogue systems"
    - "sim2real view invariant visual servoing by recurrent control"
    - "investigation of language understanding impact for reinforcement learning based dialogue systems"
    - "simpleds a simple deep reinforcement learning dialogue system"
    - "towards end to end learning for dialog state tracking and management using deep reinforcement learning"
    - "a user simulator for task completion dialogues"

Connected through hyperedge HE-6 (induced by source paper "towards better understanding of spontaneous conversations overcoming automatic speech recognition errors with intent recognition"):
  with members:
    - "composing finite state transducers on gpus"
    - "the capio 2017 conversational speech recognition system"
    - "punctuation prediction model for conversational speech"
    - "the marchex 2018 english conversational telephone speech recognition system"
    - "the microsoft 2017 conversational speech recognition system"
    - "encodingword confusion networks with recurrent neural networks for dialog state tracking"
    - "finding consensus in speech recognition word error minimization and other applications of confusion networks"

Connected through hyperedge HE-7 (induced by source paper "building chatbots from large scale domain specific knowledge bases challenges and opportunities"):
  with members:
    - "beyond word embeddings learning entity and concept representations from large scale knowledge bases"
    - "fonduer knowledge base construction from richly formatted data"
    - "effective approaches to attention based neural machine translation"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-8 (induced by source paper "gunrock a social bot for complex and engaging long conversations"):
  with members:
    - "midas a dialog act annotation scheme for open domain human machine spoken conversations"
    - "a neural conversational model"
    - "a diversity promoting objective function for neural conversation models"

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)