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: "wikiatomicedits a multilingual corpus of wikipedia edits for modeling language and discourse"
  Abstract: We release a corpus of 43 million atomic edits across 8 languages. These edits are mined from Wikipedia edit history and consist of instances in which a human editor has inserted a single contiguous phrase into, or deleted a single contiguous phrase from, an existing sentence. We use the collected data to show that the language generated during editing differs from the language that we observe in standard corpora, and that models trained on edits encode different aspects of semantics and discourse than models trained on raw, unstructured text. We release the full corpus as a resource to aid ongoing research in semantics, discourse, and representation learning.

Connected through hyperedge HE-1 (induced by source paper "automatically neutralizing subjective bias in text"):
  with members:
    - "towards controlled transformation of sentiment in sentences"
    - "black is to criminal as caucasian is to police detecting and removing multiclass bias in word embeddings"
    - "evaluating style transfer for text"
    - "identifying and reducing gender bias in word level language models"
    - "understanding undesirable word embedding associations"
    - "approaching neural grammatical error correction as a low resource machine translation task"
    - "delete retrieve generate a simple approach to sentiment and style transfer"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-2 (induced by source paper "associating natural language comment and source code entities"):
  with members:
    - "structured neural summarization"
    - "the adverse effects of code duplication in machine learning models of code"
    - "tranx a transition based neural abstract syntax parser for semantic parsing and code generation"
    - "typesql knowledge based type aware neural text to sql generation"
    - "learning to mine aligned code and natural language pairs from stack overflow"
    - "staqc a systematically mined question code dataset from stack overflow"
    - "retrieval based neural code generation"
    - "linguistically informed self attention for semantic role labeling"

Connected through hyperedge HE-3 (induced by source paper "translator2vec understanding and representing human post editors"):
  with members:
    - "recurrent neural network based user authentication for freely typed keystroke data"
    - "learning to represent edits"
    - "marian fast neural machine translation in c"
    - "attention is all you need"
    - "a practical approach to dialogue response generation in closed domains"
    - "scalable semantic matching of queries to ads in sponsored search advertising"
    - "bag of tricks for efficient text classification"
    - "a convolutional encoder model for neural machine translation"

Connected through hyperedge HE-4 (induced by source paper "learning to represent edits"):
  with members:
    - "response generation by context aware prototype editing"
    - "constrained graph variational autoencoders for molecule design"
    - "graphvae towards generation of small graphs using variational autoencoders"
    - "deep differential recurrent neural networks"
    - "tranx a transition based neural abstract syntax parser for semantic parsing and code generation"
    - "tree to tree neural networks for program translation"
    - "learning quick fixes from code repositories"
    - "generating sentences by editing prototypes"

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)