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 "can monolingual pretrained models help cross lingual classification"):
  Abstract: Multilingual pretrained language models (such as multilingual BERT) have achieved impressive results for cross-lingual transfer. However, due to the constant model capacity, multilingual pre-training usually lags behind the monolingual competitors. In this work, we present two approaches to improve zero-shot cross-lingual classification, by transferring the knowledge from monolingual pretrained models to multilingual ones. Experimental results on two cross-lingual classification benchmarks show that our methods outperform vanilla multilingual fine-tuning.

Includes members:
  Member "adversarial learning with contextual embeddings for zero resource cross lingual classification and ner":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cross lingual alignment vs joint training a comparative study and a simple unified framework")
  Member "unsupervised cross lingual representation learning at scale":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on contextual embeddings")
  Member "massively multilingual neural machine translation in the wild findings and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "beto bentz becas the surprising cross lingual effectiveness of bert":
    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 "multifit efficient multi lingual language model fine tuning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the cross lingual transferability of monolingual representations")
  Member "how multilingual is multilingual bert":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "cross lingual language model pretraining":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on contextual embeddings")
  Member "cross lingual natural language generation via pre training":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "xpersona evaluating multilingual personalized chatbot")

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)