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 "vatex a large scale high quality multilingual dataset for video and language research"):
  Abstract: We present a new large-scale multilingual video description dataset, VATEX, which contains over 41,250 videos and 825,000 captions in both English and Chinese. Among the captions, there are over 206,000 English-Chinese parallel translation pairs. Compared to the widely-used MSR-VTT dataset, VATEX is multilingual, larger, linguistically complex, and more diverse in terms of both video and natural language descriptions. We also introduce two tasks for video-and-language research based on VATEX: (1) Multilingual Video Captioning, aimed at describing a video in various languages with a compact unified captioning model, and (2) Video-guided Machine Translation, to translate a source language description into the target language using the video information as additional spatiotemporal context. Extensive experiments on the VATEX dataset show that, first, the unified multilingual model can not only produce both English and Chinese descriptions for a video more efficiently, but also offer improved performance over the monolingual models. Furthermore, we demonstrate that the spatiotemporal video context can be effectively utilized to align source and target languages and thus assist machine translation. In the end, we discuss the potentials of using VATEX for other video-and-language research.

Includes members:
  Member "probing the need for visual context in multimodal machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "don t take the easy way out ensemble based methods for avoiding known dataset biases")
  Member "video description a survey of methods datasets and evaluation metrics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multimodal matching transformer for live commenting")
  Member "nocaps novel object captioning at scale":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "say as you wish fine grained control of image caption generation with abstract scene graphs")
  Member "man moment alignment network for natural language moment retrieval via iterative graph adjustment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "where does it exist spatio temporal video grounding for multi form sentences")
  Member "learning to compose topic aware mixture of experts for zero shot video captioning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "delving deeper into the decoder for video captioning")
  Member "watch listen and describe globally and locally aligned cross modal attentions for video captioning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi modal dense video captioning")
  Member "the memad submission to the wmt18 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on architectures for including visual information in neural language models for image description")
  Member "how2 a large scale dataset for multimodal language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "looking enhances listening recovering missing speech using images")

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)