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 "factor graph attention"):
  Abstract: Dialog is an effective way to exchange information, but subtle details and nuances are extremely important. While significant progress has paved a path to address visual dialog with algorithms, details and nuances remain a challenge. Attention mechanisms have demonstrated compelling results to extract details in visual question answering and also provide a convincing framework for visual dialog due to their interpretability and effectiveness. However, the many data utilities that accompany visual dialog challenge existing attention techniques. We address this issue and develop a general attention mechanism for visual dialog which operates on any number of data utilities. To this end, we design a factor graph based attention mechanism which combines any number of utility representations. We illustrate the applicability of the proposed approach on the challenging and recently introduced VisDial datasets, outperforming recent state-of-the-art methods by 1.1% for VisDial0.9 and by 2% for VisDial1.0 on MRR. Our ensemble model improved the MRR score on VisDial1.0 by more than 6%.

Includes members:
  Member "a simple baseline for audio visual scene aware dialog":
    also connected through other hyperedges:
      (none)
  Member "diverse and coherent paragraph generation from images":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "curiosity driven reinforcement learning for diverse visual paragraph generation")
  Member "end to end audio visual scene aware dialog using multimodal attention based video features":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi step joint modality attention network for scene aware dialogue system")
  Member "visual coreference resolution in visual dialog using neural module networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "vision dialog navigation by exploring cross modal memory")
  Member "audio visual scene aware dialog avsd challenge at dstc7":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dialog system technology challenge 7")
  Member "straight to the facts learning knowledge base retrieval for factual visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ok vqa a visual question answering benchmark requiring external knowledge")
  Member "out of the box reasoning with graph convolution nets for factual visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adaptive graph convolutional network with attention graph clustering for co saliency detection")
  Member "two can play this game visual dialog with discriminative question generation and answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning to respond with stickers a framework of unifying multi modality in multi turn dialog")

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)