human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "reconstructing native language typology from foreign language usage"
  Abstract: Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language. In this work we provide empirical evidence for this process in the form of a strong correlation between language similarities derived from structural features in English as Second Language (ESL) texts and equivalent similarities obtained from the typological features of the native languages. We leverage this finding to recover native language typological similarity structure directly from ESL text, and perform prediction of typological features in an unsupervised fashion with respect to the target languages. Our method achieves 72.2% accuracy on the typology prediction task, a result that is highly competitive with equivalent methods that rely on typological resources.

Connected through hyperedge HE-1 (induced by source paper "modeling language variation and universals a survey on typological linguistics for natural language processing"):
  with members:
    - "morphological word embeddings"
    - "from phonology to syntax unsupervised linguistic typology at different levels with language embeddings"
    - "xnli evaluating cross lingual sentence representations"
    - "a deep generative model of vowel formant typology"
    - "deep contextualized word representations"
    - "deep probabilistic logic a unifying framework for indirect supervision"
    - "adversarial propagation and zero shot cross lingual transfer of word vector specialization"
    - "past present future a computational investigation of the typology of tense in 1000 languages"

Connected through hyperedge HE-2 (induced by source paper "native language cognate effects on second language lexical choice"):
  with members:
    - "contrastive analysis with predictive power typology driven estimation of grammatical error distributions in esl"

Connected through hyperedge HE-3 (induced by source paper "learning language representations for typology prediction"):
  with members:
    - "learning to generate reviews and discovering sentiment"
    - "what do neural machine translation models learn about morphology"
    - "continuous multilinguality with language vectors"
    - "survey on the use of typological information in natural language processing"
    - "toward multilingual neural machine translation with universal encoder and decoder"
    - "polyglot neural language models a case study in cross lingual phonetic representation learning"
    - "classifying syntactic regularities for hundreds of languages"
    - "what do recurrent neural network grammars learn about syntax"

Connected through hyperedge HE-4 (induced by source paper "predicting native language from gaze"):
  with members:
    - "contrastive analysis with predictive power typology driven estimation of grammatical error distributions in esl"
    - "a universal part of speech tagset"

Connected through hyperedge HE-5 (induced by source paper "found in translation reconstructing phylogenetic language trees from translations"):
  with members:
    - "the generalized robinson foulds metric"

Connected through hyperedge HE-6 (induced by source paper "survey on the use of typological information in natural language processing"):
  with members:
    - "polyglot neural language models a case study in cross lingual phonetic representation learning"
    - "classifying syntactic regularities for hundreds of languages"
    - "many languages one parser"
    - "separated by an un common language towards judgment language informed vector space modeling"
    - "autoextend extending word embeddings to embeddings for synsets and lexemes"
    - "bilingual distributed word representations from document aligned comparable data"
    - "encoding prior knowledge with eigenword embeddings"
    - "multilingual models for compositional distributed semantics"

Connected through hyperedge HE-7 (induced by source paper "classifying syntactic regularities for hundreds of languages"):
  with members:
    - "exploiting similarities among languages for machine translation"
    - "a bayesian model for discovering typological implications"

Connected through hyperedge HE-8 (induced by source paper "contrastive analysis with predictive power typology driven estimation of grammatical error distributions in esl"):
  with members:
    - "non parametric bayesian areal linguistics"

Question: Please tell me which class the center node 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)