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 "cosmo contextualized scene modeling with boltzmann machines"):
  Abstract: Scene modeling is very crucial for robots that need to perceive, reason about and manipulate the objects in their environments. In this paper, we adapt and extend Boltzmann Machines (BMs) for contextualized scene modeling. Although there are many models on the subject, ours is the first to bring together objects, relations, and affordances in a highly-capable generative model. For this end, we introduce a hybrid version of BMs where relations and affordances are introduced with shared, tri-way connections into the model. Moreover, we contribute a dataset for relation estimation and modeling studies. We evaluate our method in comparison with several baselines on object estimation, out-of-context object detection, relation estimation, and affordance estimation tasks. Moreover, to illustrate the generative capability of the model, we show several example scenes that the model is able to generate.

Includes members:
  Member "focal loss for dense object detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "object detection in optical remote sensing images a survey and a new benchmark")
  Member "a simple neural network module for relational reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "context reasoning in underwater robots using mebn":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reference model of multi entity bayesian networks for predictive situation awareness")
  Member "a deep incremental boltzmann machine for modeling context in robots":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a learning based approach to incremental context modeling in robots")
  Member "a learning based approach to incremental context modeling in robots":
    also connected through other hyperedges:
      (none)
  Member "affordancenet an end to end deep learning approach for object affordance detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dgcm net dense geometrical correspondence matching network for incremental experience based robotic grasping")
  Member "what is missing or wrong in the scene a hybrid deep boltzmann machine for contextualized scene modeling":
    also connected through other hyperedges:
      (none)
  Member "mask r cnn":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relatext exploiting visual relationships for arbitrary shaped scene text detection with graph convolutional networks")

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.RO(Robotics)