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: "pre training with whole word masking for chinese bert"
  Abstract: Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks. Recently, an upgraded version of BERT has been released with Whole Word Masking (WWM), which mitigate the drawbacks of masking partial WordPiece tokens in pre-training BERT. In this technical report, we adapt whole word masking in Chinese text, that masking the whole word instead of masking Chinese characters, which could bring another challenge in Masked Language Model (MLM) pre-training task. The proposed models are verified on various NLP tasks, across sentence-level to document-level, including machine reading comprehension (CMRC 2018, DRCD, CJRC), natural language inference (XNLI), sentiment classification (ChnSentiCorp), sentence pair matching (LCQMC, BQ Corpus), and document classification (THUCNews). Experimental results on these datasets show that the whole word masking could bring another significant gain. Moreover, we also examine the effectiveness of the Chinese pre-trained models: BERT, ERNIE, BERT-wwm, BERT-wwm-ext, RoBERTa-wwm-ext, and RoBERTa-wwm-ext-large. We release all the pre-trained models: \url{this https URL

Connected through hyperedge HE-1 (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-2 (induced by source paper "what the mask making sense of language specific bert models"):
  with members:
    - "arabert transformer based model for arabic language understanding"
    - "binary and multitask classification model for dutch anaphora resolution die dat prediction"
    - "robbert a dutch roberta based language model"
    - "a primer in bertology what we know about how bert works"
    - "camembert a tasty french language model"
    - "albert a lite bert for self supervised learning of language representations"
    - "paws x a cross lingual adversarial dataset for paraphrase identification"
    - "flaubert unsupervised language model pre training for french"

Connected through hyperedge HE-3 (induced by source paper "textbrewer an open source knowledge distillation toolkit for natural language processing"):
  with members:
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "extreme language model compression with optimal subwords and shared projections"
    - "multilingual neural machine translation with knowledge distillation"
    - "albert a lite bert for self supervised learning of language representations"
    - "improving multi task deep neural networks via knowledge distillation for natural language understanding"
    - "bam born again multi task networks for natural language understanding"
    - "preparing lessons improve knowledge distillation with better supervision"
    - "xlnet generalized autoregressive pretraining for language understanding"

Connected through hyperedge HE-4 (induced by source paper "crosswoz a large scale chinese cross domain task oriented dialogue dataset"):
  with members:
    - "convlab 2 an open source toolkit for building evaluating and diagnosing dialogue systems"
    - "multiwoz 2 1 multi domain dialogue state corrections and state tracking baselines"
    - "towards scalable multi domain conversational agents the schema guided dialogue dataset"
    - "guided dialog policy learning reward estimation for multi domain task oriented dialog"
    - "building a conversational agent overnight with dialogue self play"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "key value retrieval networks for task oriented dialogue"
    - "composite task completion dialogue policy learning via hierarchical deep reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "a bert based sentiment analysis and key entity detection approach for online financial texts"):
  with members:
    - "few shot deep adversarial learning for video based person re identification"
    - "ernie enhanced language representation with informative entities"
    - "cycle consistent deep generative hashing for cross modal retrieval"
    - "albert a lite bert for self supervised learning of language representations"
    - "cross entropy adversarial view adaptation for person re identification"
    - "roberta a robustly optimized bert pretraining approach"
    - "deep learning for sentiment analysis a survey"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-6 (induced by source paper "cluener2020 fine grained named entity recognition dataset and benchmark for chinese"):
  with members:
    - "albert a lite bert for self supervised learning of language representations"
    - "ernie 2 0 a continual pre training framework for language understanding"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "roberta a robustly optimized bert pretraining approach"
    - "learning named entity tagger using domain specific dictionary"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "f score driven max margin neural network for named entity recognition in chinese social media"
    - "bidirectional lstm crf models for sequence tagging"

Connected through hyperedge HE-7 (induced by source paper "cluecorpus2020 a large scale chinese corpus for pre traininglanguage model"):
  with members:
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "roberta a robustly optimized bert pretraining approach"
    - "glue a multi task benchmark and analysis platform for natural language understanding"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attention is all you need"
    - "a broad coverage challenge corpus for sentence understanding through inference"
    - "squad 100 000 questions for machine comprehension of text"
    - "aligning books and movies towards story like visual explanations by watching movies and reading books"

Connected through hyperedge HE-8 (induced by source paper "investigating prior knowledge for challenging chinese machine reading comprehension"):
  with members:
    - "boolq exploring the surprising difficulty of natural yes no questions"
    - "ernie enhanced representation through knowledge integration"
    - "geosqa a benchmark for scenario based question answering in the geography domain at high school level"
    - "dream a challenge dataset and models for dialogue based reading comprehension"
    - "chid a large scale chinese idiom dataset for cloze test"
    - "analogical reasoning on chinese morphological and semantic relations"
    - "exploiting sentence embedding for medical question answering"
    - "coqa a conversational question answering challenge"

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)