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 "moroco the moldavian and romanian dialectal corpus"):
  Abstract: In this work, we introduce the MOldavian and ROmanian Dialectal COrpus (MOROCO), which is freely available for download at this https URL. The corpus contains 33564 samples of text (with over 10 million tokens) collected from the news domain. The samples belong to one of the following six topics: culture, finance, politics, science, sports and tech. The data set is divided into 21719 samples for training, 5921 samples for validation and another 5924 samples for testing. For each sample, we provide corresponding dialectal and category labels. This allows us to perform empirical studies on several classification tasks such as (i) binary discrimination of Moldavian versus Romanian text samples, (ii) intra-dialect multi-class categorization by topic and (iii) cross-dialect multi-class categorization by topic. We perform experiments using a shallow approach based on string kernels, as well as a novel deep approach based on character-level convolutional neural networks containing Squeeze-and-Excitation blocks. We also present and analyze the most discriminative features of our best performing model, before and after named entity removal.

Includes members:
  Member "improving the results of string kernels in sentiment analysis and arabic dialect identification by adapting them to your test set":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transductive learning with string kernels for cross domain text classification")
  Member "automatic identification of closely related indian languages resources and experiments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "english bhojpuri smt system insights from the karaka model")
  Member "automated essay scoring with string kernels and word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "vector of locally aggregated word embeddings vlawe a novel document level representation")
  Member "unibuckernel reloaded first place in arabic dialect identification for the second year in a row":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "transductive learning with string kernels for cross domain text classification")
  Member "can string kernels pass the test of time in native language identification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transductive learning with string kernels for cross domain text classification")
  Member "speech recognition challenge in the wild arabic mgb 3":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "arabic natural language processing an overview")
  Member "language modeling with gated convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "contextual lensing of universal sentence representations")
  Member "a character level convolutional neural network for distinguishing similar languages and dialects":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "modeling global syntactic variation in english using dialect classification")

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)