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 "semi supervised confidence network aided gated attention based recurrent neural network for clickbait detection"):
  Abstract: Clickbaits are catchy headlines that are frequently used by social media outlets in order to allure its viewers into clicking them and thus leading them to dubious content. Such venal schemes thrive on exploiting the curiosity of naive social media users, directing traffic to web pages that won't be visited otherwise. In this paper, we propose a novel, semi-supervised classification based approach, that employs attentions sampled from a Gumbel-Softmax distribution to distill contexts that are fairly important in clickbait detection. An additional loss over the attention weights is used to encode prior knowledge. Furthermore, we propose a confidence network that enables learning over weak labels and improves robustness to noisy labels. We show that with merely 30% of strongly labeled samples we can achieve over 97% of the accuracy, of current state of the art methods in clickbait detection.

Includes members:
  Member "adversarial labeling for learning without labels":
    also connected through other hyperedges:
      (none)
  Member "how curiosity can be modeled for a clickbait detector":
    also connected through other hyperedges:
      (none)
  Member "clickbait detection in tweets using self attentive network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "federated hierarchical hybrid networks for clickbait detection")
  Member "clickbait click based accelerated incremental training of convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "querying zero streaming cameras")
  Member "diving deep into clickbaits who use them to what extents in which topics with what effects":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards reliable online clickbait video detection a content agnostic approach")
  Member "stop clickbait detecting and preventing clickbaits in online news media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the chameleon attack manipulating content display in online social media")
  Member "we used neural networks to detect clickbaits you won t believe what happened next":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "show attend and tell neural image caption generation with visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relationship embedded representation learning for grounding referring expressions")

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)