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: "coqa a conversational question answering challenge"
  Abstract: Humans gather information by engaging in conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. We introduce CoQA, a novel dataset for building Conversational Question Answering systems. Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage. We analyze CoQA in depth and show that conversational questions have challenging phenomena not present in existing reading comprehension datasets, e.g., coreference and pragmatic reasoning. We evaluate strong conversational and reading comprehension models on CoQA. The best system obtains an F1 score of 65.1%, which is 23.7 points behind human performance (88.8%), indicating there is ample room for improvement. We launch CoQA as a challenge to the community at this http URL

Connected through hyperedge HE-1 (induced by source paper "a survey on contextual embeddings"):
  with members:
    - "episodic memory in lifelong language learning"
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "visualizing and measuring the geometry of bert"
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "emerging cross lingual structure in pretrained language models"
    - "bert rediscovers the classical nlp pipeline"
    - "unsupervised cross lingual representation learning at scale"
    - "q bert hessian based ultra low precision quantization of bert"

Connected through hyperedge HE-2 (induced by source paper "xpersona evaluating multilingual personalized chatbot"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "natural language qa approaches using reasoning with external knowledge"):
  with members:
    - "transformers as soft reasoners over language"
    - "recent advances in natural language inference a survey of benchmarks resources and approaches"
    - "boolq exploring the surprising difficulty of natural yes no questions"
    - "piqa reasoning about physical commonsense in natural language"
    - "language models as knowledge bases"
    - "quoref a reading comprehension dataset with questions requiring coreferential reasoning"
    - "understanding roles and entities datasets and models for natural language inference"
    - "qasc a dataset for question answering via sentence composition"

Connected through hyperedge HE-4 (induced by source paper "beat the ai investigating adversarial human annotations for reading comprehension"):
  with members:
    - "hellaswag can a machine really finish your sentence"
    - "quoref a reading comprehension dataset with questions requiring coreferential reasoning"
    - "assessing the benchmarking capacity of machine reading comprehension datasets"
    - "drop a reading comprehension benchmark requiring discrete reasoning over paragraphs"
    - "learning the difference that makes a difference with counterfactually augmented data"
    - "adversarial nli a new benchmark for natural language understanding"
    - "roberta a robustly optimized bert pretraining approach"
    - "annotation artifacts in natural language inference data"

Connected through hyperedge HE-5 (induced by source paper "tydi qa a benchmark for information seeking question answering in typologically diverse languages"):
  with members:
    - "neural arabic question answering"
    - "boolq exploring the surprising difficulty of natural yes no questions"
    - "latent retrieval for weakly supervised open domain question answering"
    - "what question answering can learn from trivia nerds"
    - "question answering is a format when is it useful"
    - "korquad1 0 korean qa dataset for machine reading comprehension"
    - "drop a reading comprehension benchmark requiring discrete reasoning over paragraphs"
    - "mlqa evaluating cross lingual extractive question answering"

Connected through hyperedge HE-6 (induced by source paper "a pilot study on multiple choice machine reading comprehension for vietnamese texts"):
  with members:
    - "vietnamese transition based dependency parsing with supertag features"
    - "semeval 2017 task 3 community question answering"
    - "korquad1 0 korean qa dataset for machine reading comprehension"
    - "error analysis for vietnamese named entity recognition on deep neural network models"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "sberquad russian reading comprehension dataset description and analysis"
    - "spoken squad a study of mitigating the impact of speech recognition errors on listening comprehension"
    - "lstm easy first dependency parsing with pre trained word embeddings and character level word embeddings in vietnamese"

Connected through hyperedge HE-7 (induced by source paper "manymodalqa modality disambiguation and qa over diverse inputs"):
  with members:
    - "lxmert learning cross modality encoder representations from transformers"
    - "recipeqa a challenge dataset for multimodal comprehension of cooking recipes"
    - "know what you don t know unanswerable questions for squad"
    - "deep contextualized word representations"
    - "universal sentence encoder"
    - "adversarial tableqa attention supervision for question answering on tables"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "tvqa localized compositional video question answering"

Connected through hyperedge HE-8 (induced by source paper "ernie gen an enhanced multi flow pre training and fine tuning framework for natural language generation"):
  with members:
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "plato pre trained dialogue generation model with discrete latent variable"
    - "ernie enhanced representation through knowledge integration"
    - "spanbert improving pre training by representing and predicting spans"
    - "mass masked sequence to sequence pre training for language generation"
    - "pegasus pre training with extracted gap sentences for abstractive summarization"
    - "ernie 2 0 a continual pre training framework for language understanding"
    - "xlnet generalized autoregressive pretraining for language understanding"

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)