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 "fashion iq a new dataset towards retrieving images by natural language feedback"):
  Abstract: We contribute a new dataset and a novel method for natural language based fashion image retrieval. Unlike previous fashion datasets, we provide natural language annotations to facilitate the training of interactive image retrieval systems, as well as the commonly used attribute based labels. We propose a novel approach and empirically demonstrate that combining natural language feedback with visual attribute information results in superior user feedback modeling and retrieval performance relative to using either of these modalities. We believe that our dataset can encourage further work on developing more natural and real-world applicable conversational shopping assistants.

Includes members:
  Member "neural naturalist generating fine grained image comparisons":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reinforcing an image caption generator using off line human feedback")
  Member "robust change captioning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "say as you wish fine grained control of image caption generation with abstract scene graphs")
  Member "drill down interactive retrieval of complex scenes using natural language queries":
    also connected through other hyperedges:
      (none)
  Member "expressing visual relationships via language":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "modanet a large scale street fashion dataset with polygon annotations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural data server a large scale search engine for transfer learning data")
  Member "learning to describe differences between pairs of similar images":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "composing text and image for image retrieval an empirical odyssey":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning cross modal context graph for visual grounding")
  Member "dialog based interactive image retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi step reasoning via recurrent dual attention for visual 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)