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 "the replica dataset a digital replica of indoor spaces"):
  Abstract: We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions at room and building scale. Each scene consists of a dense mesh, high-resolution high-dynamic-range (HDR) textures, per-primitive semantic class and instance information, and planar mirror and glass reflectors. The goal of Replica is to enable machine learning (ML) research that relies on visually, geometrically, and semantically realistic generative models of the world - for instance, egocentric computer vision, semantic segmentation in 2D and 3D, geometric inference, and the development of embodied agents (virtual robots) performing navigation, instruction following, and question answering. Due to the high level of realism of the renderings from Replica, there is hope that ML systems trained on Replica may transfer directly to real world image and video data. Together with the data, we are releasing a minimal C++ SDK as a starting point for working with the Replica dataset. In addition, Replica is `Habitat-compatible', i.e. can be natively used with AI Habitat for training and testing embodied agents.

Includes members:
  Member "the robotrix an extremely photorealistic and very large scale indoor dataset of sequences with robot trajectories and interactions":
    also connected through other hyperedges:
      (none)
  Member "habitat a platform for embodied ai research":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "why build an assistant in minecraft")
  Member "interiornet mega scale multi sensor photo realistic indoor scenes dataset":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lighthouse predicting lighting volumes for spatially coherent illumination")
  Member "gibson env real world perception for embodied agents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an exploration of embodied visual exploration")
  Member "on evaluation of embodied navigation agents":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an exploration of embodied visual exploration")
  Member "matterport3d learning from rgb d data in indoor environments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an exploration of embodied visual exploration")
  Member "vision and language navigation interpreting visually grounded navigation instructions in real environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards efficient model compression via learned global ranking")
  Member "embodied question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")

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)