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: "rasa open source language understanding and dialogue management"
  Abstract: We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software. Their purpose is to make machine-learning based dialogue management and language understanding accessible to non-specialist software developers. In terms of design philosophy, we aim for ease of use, and bootstrapping from minimal (or no) initial training data. Both packages are extensively documented and ship with a comprehensive suite of tests. The code is available at this https URL

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 "a financial service chatbot based on deep bidirectional transformers"):
  with members:
    - "a comprehensive guide to bayesian convolutional neural network with variational inference"
    - "selectivenet a deep neural network with an integrated reject option"
    - "distilling task specific knowledge from bert into simple neural networks"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "an evaluation dataset for intent classification and out of scope prediction"
    - "roberta a robustly optimized bert pretraining approach"
    - "the design and implementation of xiaoice an empathetic social chatbot"
    - "sampling based bayesian inference with gradient uncertainty"

Connected through hyperedge HE-3 (induced by source paper "plato dialogue system a flexible conversational ai research platform"):
  with members:
    - "moss end to end dialog system framework with modular supervision"
    - "collaborative multi agent dialogue model training via reinforcement learning"
    - "convlab multi domain end to end dialog system platform"
    - "huggingface s transformers state of the art natural language processing"
    - "nemo a toolkit for building ai applications using neural modules"
    - "adversarial learning of task oriented neural dialog models"
    - "multi task learning for joint language understanding and dialogue state tracking"
    - "detecting offensive content in open domain conversations using two stage semi supervision"

Connected through hyperedge HE-4 (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-5 (induced by source paper "multipurpose intelligent process automation via conversational assistant"):
  with members:
    - "global to local memory pointer networks for task oriented dialogue"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "limits of end to end learning"
    - "a survey on dialogue systems recent advances and new frontiers"
    - "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning"
    - "a network based end to end trainable task oriented dialogue system"

Connected through hyperedge HE-6 (induced by source paper "dialogue transformers"):
  with members:
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "training neural response selection for task oriented dialogue systems"
    - "pretraining methods for dialog context representation learning"
    - "sparse sequence to sequence models"
    - "transformer xl attentive language models beyond a fixed length context"
    - "modeling intent dialog policies and response adaptation for goal oriented interactions"
    - "few shot generalization across dialogue tasks"
    - "glue a multi task benchmark and analysis platform for natural language understanding"

Connected through hyperedge HE-7 (induced by source paper "modeling intent dialog policies and response adaptation for goal oriented interactions"):
  with members:
    - "few shot generalization across dialogue tasks"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "tensor fusion network for multimodal sentiment analysis"
    - "starspace embed all the things"
    - "sample efficient actor critic reinforcement learning with supervised data for dialogue management"
    - "attention is all you need"
    - "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning"
    - "end to end optimization of task oriented dialogue model with deep reinforcement learning"

Connected through hyperedge HE-8 (induced by source paper "incremental improvement of a question answering system by re ranking answer candidates using machine learning"):
  with members:
    - "key value retrieval networks for task oriented dialogue"
    - "starspace embed all the things"
    - "triviaqa a large scale distantly supervised challenge dataset for reading comprehension"
    - "automatic question answering using a deep similarity neural network"
    - "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning"
    - "ask the right questions active question reformulation with reinforcement learning"
    - "reading wikipedia to answer open domain questions"
    - "squad 100 000 questions for machine comprehension of text"

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)