human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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

Includes members:
  Member "option comparison network for multiple choice reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "neuro symbolic architectures for context understanding")
  Member "ernie enhanced representation through knowledge integration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a knowledge enhanced pretraining model for commonsense story generation")
  Member "transformer xl attentive language models beyond a fixed length context":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on contextual embeddings")
  Member "ernie enhanced language representation with informative entities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on contextual embeddings")
  Member "reducing bert pre training time from 3 days to 76 minutes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "disentangling adaptive gradient methods from learning rates")
  Member "cjrc a reliable human annotated benchmark dataset for chinese judicial reading comprehension":
    also connected through other hyperedges:
      (none)
  Member "dual co matching network for multi choice reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the comparability of pre trained language models")
  Member "know what you don t know unanswerable questions for squad":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "description based text classification with reinforcement learning")

Question: Please tell me which class the source paper 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)