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 "question guided modular routing networks for visual question answering"):
  Abstract: Visual Question Answering (VQA) faces two major challenges: how to better fuse the visual and textual modalities and how to make the VQA model have the reasoning ability to answer more complex questions. In this paper, we address both challenges by proposing the novel Question Guided Modular Routing Networks (QGMRN). QGMRN can fuse the visual and textual modalities in multiple semantic levels which makes the fusion occur in a fine-grained way, it also can learn to reason by routing between the generic modules without additional supervision information or prior knowledge. The proposed QGMRN consists of three sub-networks: visual network, textual network and routing network. The routing network selectively executes each module in the visual network according to the pathway activated by the question features generated by the textual network. Experiments on the CLEVR dataset show that our model can outperform the state-of-the-art. Models and Codes will be released.

Includes members:
  Member "outrageously large neural networks the sparsely gated mixture of experts layer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "attention over parameters for dialogue systems")
  Member "modulating early visual processing by language":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "inferring and executing programs for visual reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unsupervised question decomposition for question answering")
  Member "show ask attend and answer a strong baseline for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cq vqa visual question answering on categorized questions")
  Member "mutan multimodal tucker fusion for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "component analysis for visual question answering architectures")
  Member "routing networks adaptive selection of non linear functions for multi task learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "attention over parameters for dialogue systems")
  Member "a simple neural network module for relational reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "blockdrop dynamic inference paths in residual networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "switchable precision neural networks")

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)