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 "data augmentation for neural online chat response selection"):
  Abstract: Data augmentation seeks to manipulate the available data for training to improve the generalization ability of models. We investigate two data augmentation proxies, permutation and flipping, for neural dialog response selection task on various models over multiple datasets, including both Chinese and English languages. Different from standard data augmentation techniques, our method combines the original and synthesized data for prediction. Empirical results show that our approach can gain 1 to 3 recall-at-1 points over baseline models in both full-scale and small-scale settings.

Includes members:
  Member "sharp nearby fuzzy far away how neural language models use context":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "big code big vocabulary open vocabulary models for source code")
  Member "data augmentation for low resource neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "snippext semi supervised opinion mining with augmented data")
  Member "learning to paraphrase for question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "paraphrase generation with latent bag of words")
  Member "frames a corpus for adding memory to goal oriented dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "data noising as smoothing in neural network language models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning data manipulation for augmentation and weighting")
  Member "semi supervised qa with generative domain adaptive nets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "description based text classification with reinforcement learning")
  Member "robust multilingual part of speech tagging via adversarial training":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "linguistic knowledge and transferability of contextual representations")
  Member "fine grained analysis of sentence embeddings using auxiliary prediction tasks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sentence analogies exploring linguistic relationships and regularities in sentence embeddings")

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)