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 "vision dialog navigation by exploring cross modal memory"):
  Abstract: Vision-dialog navigation posed as a new holy-grail task in vision-language disciplinary targets at learning an agent endowed with the capability of constant conversation for help with natural language and navigating according to human responses. Besides the common challenges faced in visual language navigation, vision-dialog navigation also requires to handle well with the language intentions of a series of questions about the temporal context from dialogue history and co-reasoning both dialogs and visual scenes. In this paper, we propose the Cross-modal Memory Network (CMN) for remembering and understanding the rich information relevant to historical navigation actions. Our CMN consists of two memory modules, the language memory module (L-mem) and the visual memory module (V-mem). Specifically, L-mem learns latent relationships between the current language interaction and a dialog history by employing a multi-head attention mechanism. V-mem learns to associate the current visual views and the cross-modal memory about the previous navigation actions. The cross-modal memory is generated via a vision-to-language attention and a language-to-vision attention. Benefiting from the collaborative learning of the L-mem and the V-mem, our CMN is able to explore the memory about the decision making of historical navigation actions which is for the current step. Experiments on the CVDN dataset show that our CMN outperforms the previous state-of-the-art model by a significant margin on both seen and unseen environments.

Includes members:
  Member "reasoning visual dialogs with structural and partial observations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hierarchical human parsing with typed part relation reasoning")
  Member "dual attention networks for visual reference resolution in visual dialog":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi step joint modality attention network for scene aware dialogue system")
  Member "vision language navigation with self supervised auxiliary reasoning tasks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "from seeing to moving a survey on learning for visual indoor navigation vin")
  Member "multi step reasoning via recurrent dual attention for visual dialog":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi step joint modality attention network for scene aware dialogue system")
  Member "self monitoring navigation agent via auxiliary progress estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "from seeing to moving a survey on learning for visual indoor navigation vin")
  Member "factor graph attention":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi step reasoning via recurrent dual attention for visual dialog")
  Member "learning to navigate unseen environments back translation with environmental dropout":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "from seeing to moving a survey on learning for visual indoor navigation vin")
  Member "reinforced cross modal matching and self supervised imitation learning for vision language navigation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "from seeing to moving a survey on learning for visual indoor navigation vin")

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)