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 "good enough compositional data augmentation"):
  Abstract: We propose a simple data augmentation protocol aimed at providing a compositional inductive bias in conditional and unconditional sequence models. Under this protocol, synthetic training examples are constructed by taking real training examples and replacing (possibly discontinuous) fragments with other fragments that appear in at least one similar environment. The protocol is model-agnostic and useful for a variety of tasks. Applied to neural sequence-to-sequence models, it reduces relative error rate by up to 87% on problems from the diagnostic SCAN tasks and 16% on a semantic parsing task. Applied to n-gram language modeling, it reduces perplexity by roughly 1% on small datasets in several languages.

Includes members:
  Member "eda easy data augmentation techniques for boosting performance on text classification tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "snippext semi supervised opinion mining with augmented data")
  Member "human few shot learning of compositional instructions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning compositional rules via neural program synthesis")
  Member "learning data manipulation for augmentation and weighting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data augmentation using pre trained transformer models")
  Member "improving text to sql evaluation methodology":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "scalable neural methods for reasoning with a symbolic knowledge base")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "jump to better conclusions scan both left and right":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "linguistic generalization and compositionality in modern artificial neural networks")
  Member "deep learning a critical appraisal":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "on the state of the art of evaluation in neural language models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

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)