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 "vqd visual query detection in natural scenes"):
  Abstract: We propose Visual Query Detection (VQD), a new visual grounding task. In VQD, a system is guided by natural language to localize a \emph{variable} number of objects in an image. VQD is related to visual referring expression recognition, where the task is to localize only \emph{one} object. We describe the first dataset for VQD and we propose baseline algorithms that demonstrate the difficulty of the task compared to referring expression recognition.

Includes members:
  Member "panoptic segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "answer them all toward universal visual question answering models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "in defense of grid features for visual question answering")
  Member "tallyqa answering complex counting questions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "answer them all toward universal visual question answering models")
  Member "dvqa understanding data visualizations via question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "manymodalqa modality disambiguation and qa over diverse inputs")
  Member "an analysis of visual question answering algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "visual question answering on 360 deg images")
  Member "a joint speaker listener reinforcer model for referring expressions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "clevr a diagnostic dataset for compositional language and elementary visual reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "combining multiple cues for visual madlibs question answering":
    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)