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 "connecting vision and language with localized narratives"):
  Abstract: We propose Localized Narratives, an efficient way to collect image captions with dense visual grounding. We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing. Since the voice and the mouse pointer are synchronized, we can localize every single word in the description. This dense visual grounding takes the form of a mouse trace segment per word and is unique to our data. We annotate 500k images with Localized Narratives: the whole COCO dataset and 380k images of the Open Images dataset. We provide an extensive analysis of these annotations, which we will release early 2020. Moreover, we demonstrate the utility of our data on two applications which benefit from our mouse trace: controlled image captioning and image generation.

Includes members:
  Member "dense relational captioning triple stream networks for relationship based captioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "counterfactual critic multi agent training for scene graph generation")
  Member "neural sequential phrase grounding seqground":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cops ref a new dataset and task on compositional referring expression comprehension")
  Member "taking a hint leveraging explanations to make vision and language models more grounded":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")
  Member "gqa a new dataset for real world visual reasoning and compositional question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unbiased scene graph generation from biased training")
  Member "multimodal transformer with multi view visual representation for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "normalized and geometry aware self attention network for image captioning")
  Member "large scale interactive object segmentation with human annotators":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "f brs rethinking backpropagating refinement for interactive segmentation")
  Member "semantic image synthesis with spatially adaptive normalization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "context and attribute grounded dense captioning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to collocate neural modules for image captioning")

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)