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 "open the boxes of words incorporating sememes into textual adversarial attack"):
  Abstract: Adversarial attack is carried out to reveal the vulnerability of deep neural networks. Word substitution is a class of effective adversarial textual attack method, which has been extensively explored. However, all existing studies utilize word embeddings or thesauruses to find substitutes. In this paper, we incorporate sememes, the minimum semantic units, into adversarial attack. We propose an efficient sememe-based word substitution strategy and integrate it into a genetic attack algorithm. In experiments, we employ our attack method to attack LSTM and BERT on both Chinese and English sentiment analysis as well as natural language inference benchmark datasets. Experimental results demonstrate our model achieves better attack success rates and less modification than the baseline methods based on word embedding or synonym. Furthermore, we find our attack model can bring more robustness enhancement to the target model with adversarial training.

Includes members:
  Member "openhownet an open sememe based lexical knowledge base":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi channel reverse dictionary model")
  Member "adversarial example generation with syntactically controlled paraphrase networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stress test evaluation of transformer based models in natural language understanding tasks")
  Member "language modeling with sparse product of sememe experts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lexical sememe prediction using dictionary definitions by capturing local semantic correspondence")
  Member "generating natural language adversarial examples":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "humpty dumpty controlling word meanings via corpus poisoning")
  Member "adventure adversarial training for textual entailment with knowledge guided examples":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a cross sentence latent variable model for semi supervised text sequence matching")
  Member "generating natural adversarial examples":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robustness verification for transformers")
  Member "intriguing properties of neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "adversarial ranking attack and defense")

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)