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 "deep latent space learning for cross modal mapping of audio and visual signals"):
  Abstract: We propose a novel deep training algorithm for joint representation of audio and visual information which consists of a single stream network (SSNet) coupled with a novel loss function to learn a shared deep latent space representation of multimodal information. The proposed framework characterizes the shared latent space by leveraging the class centers which helps to eliminate the need for pairwise or triplet supervision. We quantitatively and qualitatively evaluate the proposed approach on VoxCeleb, a benchmarks audio-visual dataset on a multitude of tasks including cross-modal verification, cross-modal matching, and cross-modal retrieval. State-of-the-art performance is achieved on cross-modal verification and matching while comparable results are observed on the remaining applications. Our experiments demonstrate the effectiveness of the technique for cross-modal biometric applications.

Includes members:
  Member "seeing voices and hearing faces cross modal biometric matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "unsupervised any to many audiovisual synthesis via exemplar autoencoders")
  Member "disjoint mapping network for cross modal matching of voices and faces":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "speech2face learning the face behind a voice")
  Member "audio visual event localization in unconstrained videos":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stavis spatio temporal audiovisual saliency network")
  Member "learnable pins cross modal embeddings for person identity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adversarial representation learning for text to image matching")
  Member "git loss for deep face recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "few shot learning for domain specfic fine grained image classfication")
  Member "voxceleb2 deep speaker recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "everybody s talkin let me talk as you want")
  Member "on learning associations of faces and voices":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning to localize sound sources in visual scenes analysis and applications")
  Member "look listen and learn":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning representations by predicting bags of visual words")

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)