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 "captioning images taken by people who are blind"):
  Abstract: While an important problem in the vision community is to design algorithms that can automatically caption images, few publicly-available datasets for algorithm development directly address the interests of real users. Observing that people who are blind have relied on (human-based) image captioning services to learn about images they take for nearly a decade, we introduce the first image captioning dataset to represent this real use case. This new dataset, which we call VizWiz-Captions, consists of over 39,000 images originating from people who are blind that are each paired with five captions. We analyze this dataset to (1) characterize the typical captions, (2) characterize the diversity of content found in the images, and (3) compare its content to that found in eight popular vision datasets. We also analyze modern image captioning algorithms to identify what makes this new dataset challenging for the vision community. We publicly-share the dataset with captioning challenge instructions at this https URL

Includes members:
  Member "attention on attention for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deconfounded image captioning a causal retrospect")
  Member "nocaps novel object captioning at scale":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "say as you wish fine grained control of image caption generation with abstract scene graphs")
  Member "vizwiz grand challenge answering visual questions from blind people":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "in defense of grid features for visual question answering")
  Member "a comprehensive survey of deep learning for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "language is power representing states using natural language in reinforcement learning")
  Member "auto encoding scene graphs for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "engaging image captioning via personality":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint reasoning for multi faceted commonsense knowledge")
  Member "speech coco 600k visually grounded spoken captions aligned to mscoco data set":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "models of visually grounded speech signal pay attention to nouns a bilingual experiment on english and japanese")
  Member "bottom up and top down attention for image captioning and visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "ha ccn hierarchical attention based crowd counting network")

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)