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: "the second conversational intelligence challenge convai2"
  Abstract: We describe the setting and results of the ConvAI2 NeurIPS competition that aims to further the state-of-the-art in open-domain chatbots. Some key takeaways from the competition are: (1) pretrained Transformer variants are currently the best performing models on this task, (2) but to improve performance on multi-turn conversations with humans, future systems must go beyond single word metrics like perplexity to measure the performance across sequences of utterances (conversations)—in terms of repetition, consistency and balance of dialogue acts (e.g. how many questions asked vs. answered).

Connected through hyperedge HE-1 (induced by source paper "attention over parameters for dialogue systems"):
  with members:
    - "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"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "importance of search and evaluation strategies in neural dialogue modeling"

Connected through hyperedge HE-2 (induced by source paper "xpersona evaluating multilingual personalized chatbot"):
  with members:
    - "towards a human like open domain chatbot"
    - "named entity recognition on code switched data overview of the calcs 2018 shared task"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "code switched language models using neural based synthetic data from parallel sentences"
    - "unsupervised cross lingual representation learning at scale"
    - "camembert a tasty french language model"
    - "zero shot cross lingual dialogue systems with transferable latent variables"
    - "cross lingual ability of multilingual bert an empirical study"

Connected through hyperedge HE-3 (induced by source paper "detecting asks in se attacks impact of linguistic and structural knowledge"):
  with members:
    - "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions"
    - "investigating evaluation of open domain dialogue systems with human generated multiple references"
    - "allennlp a deep semantic natural language processing platform"
    - "neural approaches to conversational ai"
    - "augmenting neural response generation with context aware topical attention"

Connected through hyperedge HE-4 (induced by source paper "the dialogue dodecathlon open domain knowledge and image grounded conversational agents"):
  with members:
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "real time inference in multi sentence tasks with deep pretrained transformers"
    - "lxmert learning cross modality encoder representations from transformers"
    - "the curious case of neural text degeneration"
    - "conversing by reading contentful neural conversation with on demand machine reading"
    - "real or fake learning to discriminate machine from human generated text"
    - "ctrl a conditional transformer language model for controllable generation"

Connected through hyperedge HE-5 (induced by source paper "moel mixture of empathetic listeners"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "global to local memory pointer networks for task oriented dialogue"
    - "happybot generating empathetic dialogue responses by improving user experience look ahead"
    - "deepcopy grounded response generation with hierarchical pointer networks"
    - "importance of search and evaluation strategies in neural dialogue modeling"
    - "aiming to know you better perhaps makes me a more engaging dialogue partner"
    - "skeleton to response dialogue generation guided by retrieval memory"
    - "retrieve and refine improved sequence generation models for dialogue"

Connected through hyperedge HE-6 (induced by source paper "learning to speak and act in a fantasy text adventure game"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "neural symbolic vqa disentangling reasoning from vision and language understanding"
    - "game based video context dialogue"
    - "textworld a learning environment for text based games"
    - "talk the walk navigating new york city through grounded dialogue"
    - "training millions of personalized dialogue agents"
    - "building generalizable agents with a realistic and rich 3d environment"
    - "wizard of wikipedia knowledge powered conversational agents"

Connected through hyperedge HE-7 (induced by source paper "neural text generation with unlikelihood training"):
  with members:
    - "fairseq a fast extensible toolkit for sequence modeling"
    - "the curious case of neural text degeneration"
    - "negative training for neural dialogue response generation"
    - "acute eval improved dialogue evaluation with optimized questions and multi turn comparisons"
    - "what makes a good conversation how controllable attributes affect human judgments"
    - "importance of search and evaluation strategies in neural dialogue modeling"
    - "retrieve and refine improved sequence generation models for dialogue"
    - "learning to write with cooperative discriminators"

Connected through hyperedge HE-8 (induced by source paper "bart denoising sequence to sequence pre training for natural language generation translation and comprehension"):
  with members:
    - "pre trained language model representations for language generation"
    - "spanbert improving pre training by representing and predicting spans"
    - "mass masked sequence to sequence pre training for language generation"
    - "albert a lite bert for self supervised learning of language representations"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "cross lingual language model pretraining"
    - "text summarization with pretrained encoders"
    - "roberta a robustly optimized bert pretraining approach"

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.AI(Artificial Intelligence)