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 "xcmrc evaluating cross lingual machine reading comprehension"):
  Abstract: We present XCMRC, the first public cross-lingual language understanding (XLU) benchmark which aims to test machines on their cross-lingual reading comprehension ability. To be specific, XCMRC is a Cross-lingual Cloze-style Machine Reading Comprehension task which requires the reader to fill in a missing word (we additionally provide ten noun candidates) in a sentence written in target language (English / Chinese) by reading a given passage written in source language (Chinese / English). Chinese and English are rich-resource language pairs, in order to study low-resource cross-lingual machine reading comprehension (XMRC), besides defining the common XCMRC task which has no restrictions on use of external language resources, we also define the pseudo low-resource XCMRC task by limiting the language resources to be used. In addition, we provide two baselines for common XCMRC task and two for pseudo XCMRC task respectively. We also provide an upper bound baseline for both tasks. We found that for common XCMRC task, translation-based method and multilingual sentence encoder-based method can obtain reasonable performance but still have much room for improvement. As for pseudo low-resource XCMRC task, due to strict restrictions on the use of language resources, our two approaches are far below the upper bound so there are many challenges ahead.

Includes members:
  Member "a corpus for multilingual document classification in eight languages":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beto bentz becas the surprising cross lingual effectiveness of bert")
  Member "xnli evaluating cross lingual sentence representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "know what you don t know unanswerable questions for squad":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "description based text classification with reinforcement learning")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "an empirical analysis of nmt derived interlingual embeddings and their use in parallel sentence identification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "massively multilingual document alignment with cross lingual sentence mover s distance")
  Member "supervised learning of universal sentence representations from natural language inference data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on contextual embeddings")
  Member "race large scale reading comprehension dataset from examinations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reclor a reading comprehension dataset requiring logical reasoning")
  Member "triviaqa a large scale distantly supervised challenge dataset for reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a study of the tasks and models in machine reading comprehension")

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)