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 "m vad names a dataset for video captioning with naming"):
  Abstract: Current movie captioning architectures are not capable of mentioning characters with their proper name, replacing them with a generic “someone” tag. The lack of movie description datasets with characters’ visual annotations surely plays a relevant role in this shortage. Recently, we proposed to extend the M-VAD dataset by introducing such information. In this paper, we present an improved version of the dataset, namely M-VAD Names, and its semi-automatic annotation procedure. The resulting dataset contains 63 k visual tracks and 34 k textual mentions, all associated with character identities. To showcase the features of the dataset and quantify the complexity of the naming task, we investigate multimodal architectures to replace the “someone” tags with proper character names in existing video captions. The evaluation is further extended by testing this application on videos outside of the M-VAD Names dataset.

Includes members:
  Member "end to end face detection and cast grouping in movies using erd h o s r e nyi clustering":
    also connected through other hyperedges:
      (none)
  Member "generating descriptions with grounded and co referenced people":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "visual grounding in video for unsupervised word translation")
  Member "speaking the same language matching machine to human captions by adversarial training":
    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 "moviegraphs towards understanding human centric situations from videos":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning diverse fashion collocation by neural graph filtering")
  Member "dense captioning events in videos":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi modal dense video captioning")
  Member "learning from video and text via large scale discriminative clustering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "end to end learning of visual representations from uncurated instructional videos")
  Member "hierarchical boundary aware neural encoder for video captioning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi modal dense video captioning")
  Member "improving lstm based video description with linguistic knowledge mined from text":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "augmenting neural machine translation with knowledge graphs")

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)