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 "referring to objects in videos using spatio temporal identifying descriptions"):
  Abstract: This paper presents a new task, the grounding of spatio-temporal identifying descriptions in videos. Previous work suggests potential bias in existing datasets and emphasizes the need for a new data creation schema to better model linguistic structure. We introduce a new data collection scheme based on grammatical constraints for surface realization to enable us to investigate the problem of grounding spatio-temporal identifying descriptions in videos. We then propose a two-stream modular attention network that learns and grounds spatio-temporal identifying descriptions based on appearance and motion. We show that motion modules help to ground motion-related words and also help to learn in appearance modules because modular neural networks resolve task interference between modules. Finally, we propose a future challenge and a need for a robust system arising from replacing ground truth visual annotations with automatic video object detector and temporal event localization.

Includes members:
  Member "mattnet modular attention network for referring expression comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "visual referring expression recognition what do systems actually learn":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "challenges and prospects in vision and language research")
  Member "tvqa localized compositional video question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hierarchical conditional relation networks for video question answering")
  Member "actor and action video segmentation from a sentence":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modularized textual grounding for counterfactual resilience")
  Member "flow guided feature aggregation for video object detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mast a memory augmented self supervised tracker")
  Member "obj2text generating visually descriptive language from object layouts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "image captioning with unseen objects")
  Member "dense captioning events in videos":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi modal dense video captioning")
  Member "ava a video dataset of spatio temporally localized atomic visual actions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "spatio temporal ranked attention networks for video captioning")

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)