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 "sketch less for more on the fly fine grained sketch based image retrieval"):
  Abstract: Fine-grained sketch-based image retrieval (FG-SBIR) addresses the problem of retrieving a particular photo instance given a user's query sketch. Its widespread applicability is however hindered by the fact that drawing a sketch takes time, and most people struggle to draw a complete and faithful sketch. In this paper, we reformulate the conventional FG-SBIR framework to tackle these challenges, with the ultimate goal of retrieving the target photo with the least number of strokes possible. We further propose an on-the-fly design that starts retrieving as soon as the user starts drawing. To accomplish this, we devise a reinforcement learning-based cross-modal retrieval framework that directly optimizes rank of the ground-truth photo over a complete sketch drawing episode. Additionally, we introduce a novel reward scheme that circumvents the problems related to irrelevant sketch strokes, and thus provides us with a more consistent rank list during the retrieval. We achieve superior early-retrieval efficiency over state-of-the-art methods and alternative baselines on two publicly available fine-grained sketch retrieval datasets.

Includes members:
  Member "semantically tied paired cycle consistency for zero shot sketch based image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning robust representations via multi view information bottleneck")
  Member "semantic aware knowledge preservation for zero shot sketch based image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bi directional domain translation for zero shot sketch based image retrieval")
  Member "livesketch query perturbations for guided sketch based visual search":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fine grained instance level sketch based video retrieval")
  Member "doodle to search practical zero shot sketch based image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep self supervised representation learning for free hand sketch")
  Member "interactive sketch fill multiclass sketch to image translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep plastic surgery robust and controllable image editing with human drawn sketches")
  Member "sodeep a sorting deep net to learn ranking loss surrogates":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimizing rank based metrics with blackbox differentiation")
  Member "pluralistic image completion":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grounded and controllable image completion by incorporating lexical semantics")
  Member "goal driven sequential data abstraction":
    also connected through other hyperedges:
      (none)

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)