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 "sketchformer transformer based representation for sketched structure"):
  Abstract: Sketchformer is a novel transformer-based representation for encoding free-hand sketches input in a vector form, i.e. as a sequence of strokes. Sketchformer effectively addresses multiple tasks: sketch classification, sketch based image retrieval (SBIR), and the reconstruction and interpolation of sketches. We report several variants exploring continuous and tokenized input representations, and contrast their performance. Our learned embedding, driven by a dictionary learning tokenization scheme, yields state of the art performance in classification and image retrieval tasks, when compared against baseline representations driven by LSTM sequence to sequence architectures: SketchRNN and derivatives. We show that sketch reconstruction and interpolation are improved significantly by the Sketchformer embedding for complex sketches with longer stroke sequences.

Includes members:
  Member "livesketch query perturbations for guided sketch based visual search":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sketch less for more on the fly fine grained sketch based image retrieval")
  Member "transformer xl attentive language models beyond a fixed length context":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on contextual embeddings")
  Member "doodle to search practical zero shot sketch based image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep self supervised representation learning for free hand sketch")
  Member "image transformer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adversarial code learning for image generation")
  Member "learning deep sketch abstraction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep self supervised representation learning for free hand sketch")
  Member "sketchmate deep hashing for million scale human sketch retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep self supervised representation learning for free hand sketch")
  Member "learning to sketch with shortcut cycle consistency":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sketch less for more on the fly fine grained sketch based image retrieval")
  Member "sketch r2cnn an attentive network for vector sketch recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep self supervised representation learning for free hand sketch")

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.CV(Computer Vision and Pattern Recognition)