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 "the conll sigmorphon 2018 shared task universal morphological reinflection"):
  Abstract: The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphological generation featured data sets from 103 typologically diverse languages. Apart from extending the number of languages involved in earlier supervised tasks of generating inflected forms, this year the shared task also featured a new second task which asked participants to inflect words in sentential context, similar to a cloze task. This second task featured seven languages. Task 1 received 27 submissions and task 2 received 6 submissions. Both tasks featured a low, medium, and high data condition. Nearly all submissions featured a neural component and built on highly-ranked systems from the earlier 2017 shared task. In the inflection task (task 1), 41 of the 52 languages present in last year's inflection task showed improvement by the best systems in the low-resource setting. The cloze task (task 2) proved to be difficult, and few submissions managed to consistently improve upon both a simple neural baseline system and a lemma-repeating baseline.

Includes members:
  Member "unimorph 2 0 universal morphology":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "linspector multilingual probing tasks for word representations")
  Member "marrying universal dependencies and universal morphology":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linspector multilingual probing tasks for word representations")
  Member "unsupervised disambiguation of syncretism in inflected lexicons":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "morphological irregularity correlates with frequency")
  Member "finding the way from a to a sub character morphological inflection for the sigmorphon 2018 shared task":
    also connected through other hyperedges:
      (none)
  Member "copenhagen at conll sigmorphon 2018 multilingual inflection in context with explicit morphosyntactic decoding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "contextualization of morphological inflection")
  Member "a structured variational autoencoder for contextual morphological inflection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a probabilistic semi supervised approach to multi task human activity modeling")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "align and copy uzh at sigmorphon 2017 shared task for morphological reinflection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exact hard monotonic attention for character level transduction")

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)