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 "diverse and coherent paragraph generation from images"):
  Abstract: Paragraph generation from images, which has gained popularity recently, is an important task for video summarization, editing, and support of the disabled. Traditional image captioning methods fall short on this front, since they aren't designed to generate long informative descriptions. Moreover, the vanilla approach of simply concatenating multiple short sentences, possibly synthesized from a classical image captioning system, doesn't embrace the intricacies of paragraphs: coherent sentences, globally consistent structure, and diversity. To address those challenges, we propose to augment paragraph generation techniques with 'coherence vectors', 'global topic vectors', and modeling of the inherent ambiguity of associating paragraphs with images, via a variational auto-encoder formulation. We demonstrate the effectiveness of the developed approach on two datasets, outperforming existing state-of-the-art techniques on both.

Includes members:
  Member "two can play this game visual dialog with discriminative question generation and answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to respond with stickers a framework of unifying multi modality in multi turn dialog")
  Member "self normalizing neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "soft root sign activation function")
  Member "convolutional image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "latent normalizing flows for many to many cross domain mappings")
  Member "diverse and accurate image description using a variational auto encoder with an additive gaussian encoding space":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "latent normalizing flows for many to many cross domain mappings")
  Member "creativity generating diverse questions using variational autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "high order attention models for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "recurrent topic transition gan for visual paragraph generation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust explanations for visual question answering")
  Member "towards diverse and natural image descriptions via a conditional gan":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "posenet3d unsupervised 3d human shape and pose estimation")

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)