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 "excl extractive clip localization using natural language descriptions"):
  Abstract: The task of retrieving clips within videos based on a given natural language query requires cross-modal reasoning over multiple frames. Prior approaches such as sliding window classifiers are inefficient, while text-clip similarity driven ranking-based approaches such as segment proposal networks are far more complicated. In order to select the most relevant video clip corresponding to the given text description, we propose a novel extractive approach that predicts the start and end frames by leveraging cross-modal interactions between the text and video - this removes the need to retrieve and re-rank multiple proposal segments. Using recurrent networks we encode the two modalities into a joint representation which is then used in different variants of start-end frame predictor networks. Through extensive experimentation and ablative analysis, we demonstrate that our simple and elegant approach significantly outperforms state of the art on two datasets and has comparable performance on a third.

Includes members:
  Member "man moment alignment network for natural language moment retrieval via iterative graph adjustment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "where does it exist spatio temporal video grounding for multi form sentences")
  Member "multilevel language and vision integration for text to clip retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "where does it exist spatio temporal video grounding for multi form sentences")
  Member "quo vadis action recognition a new model and the kinetics dataset":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transformation based adversarial video prediction on large scale data")
  Member "dense captioning events in videos":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi modal dense video captioning")
  Member "r c3d region convolutional 3d network for temporal activity detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "weakly supervised temporal action localization using deep metric learning")
  Member "tall temporal activity localization via language query":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "where does it exist spatio temporal video grounding for multi form sentences")
  Member "reading wikipedia to answer open domain questions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "description based text classification with reinforcement learning")
  Member "localizing moments in video with natural language":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "where does it exist spatio temporal video grounding for multi form sentences")

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.CL(Computation and Language)