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 "visual question generation as dual task of visual question answering"):
  Abstract: Recently visual question answering (VQA) and visual question generation (VQG) are two trending topics in the computer vision, which have been explored separately. In this work, we propose an end-to-end unified framework, the Invertible Question Answering Network (iQAN), to leverage the complementary relations between questions and answers in images by jointly training the model on VQA and VQG tasks. Corresponding parameter sharing scheme and regular terms are proposed as constraints to explicitly leverage Q,A's dependencies to guide the training process. After training, iQAN can take either question or answer as input, then output the counterpart. Evaluated on the large-scale visual question answering datasets CLEVR and VQA2, our iQAN improves the VQA accuracy over the baselines. We also show the dual learning framework of iQAN can be generalized to other VQA architectures and consistently improve the results over both the VQA and VQG tasks.

Includes members:
  Member "mutan multimodal tucker fusion for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "component analysis for visual question answering architectures")
  Member "creativity generating diverse questions using variational autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "question answering and question generation as dual tasks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asking questions the human way scalable question answer generation from text corpus")
  Member "hadamard product for low rank bilinear pooling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "component analysis for visual question answering architectures")
  Member "generating factoid questions with recurrent neural networks the 30m factoid question answer corpus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "asking questions the human way scalable question answer generation from text corpus")
  Member "clevr a diagnostic dataset for compositional language and elementary visual reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "3d dynamic scene graphs actionable spatial perception with places objects and humans")
  Member "hierarchical question image co attention for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "generating natural questions about an image":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")

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)