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 "perceptual vector quantization for video coding"):
  Abstract: This paper applies energy conservation principles to the Daala video codec using gain-shape vector quantization to encode a vector of AC coefficients as a length (gain) and direction (shape). The technique originates from the CELT mode of the Opus audio codec, where it is used to conserve the spectral envelope of an audio signal. Conserving energy in video has the potential to preserve textures rather than low-passing them. Explicitly quantizing a gain allows a simple contrast masking model with no signaling cost. Vector quantizing the shape keeps the number of degrees of freedom the same as scalar quantization, avoiding redundancy in the representation. We demonstrate how to predict the vector by transforming the space it is encoded in, rather than subtracting off the predictor, which would make energy conservation impossible. We also derive an encoding of the vector-quantized codewords that takes advantage of their non-uniform distribution. We show that the resulting technique outperforms scalar quantization by an average of 0.90 dB on still images, equivalent to a 24.8% reduction in bitrate at equal quality, while for videos, the improvement averages 0.83 dB, equivalent to a 13.7% reduction in bitrate.

Includes members:
  Member "high quality low delay music coding in the opus codec":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improving networked music performance systems using application network collaboration")
  Member "a high quality speech and audio codec with less than 10 ms delay":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "high quality low delay music coding in the opus codec")

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.MM(Multimedia)