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 "sequential attention gan for interactive image editing via dialogue"):
  Abstract: We introduce a new task - Interactive Image Editing via conversational language, where users can guide an agent to edit images via multi-turn dialogue. In each dialogue turn, the agent takes a source image and a natural language description as the input, and generates a modified image following the textual description. Two new datasets are introduced for this task (Zap-Seq and DeepFashion-Seq), which contain multi-turn dialog sessions with crowdsourced image-description sequences. The main challenges in this sequential and interactive image generation task are two-fold: 1) contextual consistency between a generated image and the given textual description; 2) step-by-step region-level modification to maintain visual consistency across the image sequence. To address these challenges, we propose a novel Sequential Attention Generative Adversarial Network (SeqAttnGAN) framework, which applies a neural state tracker to encode the previous image and the textual description in each dialogue turn, and uses a GAN framework to generate a modified version of the image that is consistent with the dialogue context and preceding images. To achieve better region-specific refinement, we also introduce a sequential attention mechanism into the model. Experiments on Zap-Seq and DeepFashion-Seq datasets show that the proposed SeqAttnGAN model outperforms state-of-the-art approaches on the interactive image editing task across all evaluation metrics on visual quality, image sequence coherence and text-image consistency.

Includes members:
  Member "learning to globally edit images with textual description":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "text adaptive generative adversarial networks manipulating images with natural language":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "variational hetero encoder randomized gans for joint image text modeling")
  Member "pedestrian synthesis gan generating pedestrian data in real scene and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pmc gans generating multi scale high quality pedestrian with multimodal cascaded gans")
  Member "neural approaches to conversational ai":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "attention over parameters for dialogue systems")
  Member "the neural painter multi turn image generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "c4synth cross caption cycle consistent text to image synthesis")
  Member "dialog based interactive image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi step reasoning via recurrent dual attention for visual dialog")
  Member "storygan a sequential conditional gan for story visualization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "object centric image generation from layouts")
  Member "image grounded conversations multimodal context for natural question and response generation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "low resource knowledge grounded dialogue generation")

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)