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 "entity projection via machine translation for cross lingual ner"):
  Abstract: Although over 100 languages are supported by strong off-the-shelf machine translation systems, only a subset of them possess large annotated corpora for named entity recognition. Motivated by this fact, we leverage machine translation to improve annotation-projection approaches to cross-lingual named entity recognition. We propose a system that improves over prior entity-projection methods by: (a) leveraging machine translation systems twice: first for translating sentences and subsequently for translating entities; (b) matching entities based on orthographic and phonetic similarity; and (c) identifying matches based on distributional statistics derived from the dataset. Our approach improves upon current state-of-the-art methods for cross-lingual named entity recognition on 5 diverse languages by an average of 4.1 points. Further, our method achieves state-of-the-art F_1 scores for Armenian, outperforming even a monolingual model trained on Armenian source data.

Includes members:
  Member "pioner datasets and baselines for armenian named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "word embeddings for the armenian language intrinsic and extrinsic evaluation")
  Member "adapting word embeddings to new languages with morphological and phonological subword representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "language independent tokenisation rivals language specific tokenisation for word similarity prediction")
  Member "reporting score distributions makes a difference performance study of lstm networks for sequence tagging":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards the systematic reporting of the energy and carbon footprints of machine learning")
  Member "weakly supervised cross lingual named entity recognition via effective annotation and representation projection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "xpersona evaluating multilingual personalized chatbot")
  Member "the iit bombay english hindi parallel corpus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pmindia a collection of parallel corpora of languages of india")
  Member "word translation without parallel data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep graph matching consensus")
  Member "neural architectures for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "knowledge graphs")
  Member "google s neural machine translation system bridging the gap between human and machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "automl zero evolving machine learning algorithms from scratch")

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)