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 "vq wav2vec self supervised learning of discrete speech representations"):
  Abstract: We propose vq-wav2vec to learn discrete representations of audio segments through a wav2vec-style self-supervised context prediction task. The algorithm uses either a gumbel softmax or online k-means clustering to quantize the dense representations. Discretization enables the direct application of algorithms from the NLP community which require discrete inputs. Experiments show that BERT pre-training achieves a new state of the art on TIMIT phoneme classification and WSJ speech recognition.

Includes members:
  Member "unsupervised acoustic unit discovery for speech synthesis using discrete latent variable neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning hierarchical discrete linguistic units from visually grounded speech")
  Member "fairseq a fast extensible toolkit for sequence modeling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "train large then compress rethinking model size for efficient training and inference of transformers")
  Member "transformers with convolutional context for asr":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a simplified fully quantized transformer for end to end speech recognition")
  Member "on the choice of modeling unit for sequence to sequence speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "effectiveness of self supervised pre training for speech recognition")
  Member "vqvae unsupervised unit discovery and multi scale code2spec inverter for zerospeech challenge 2019":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "speech to speech translation between untranscribed unknown languages")
  Member "pre trained language model representations for language generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "spanbert improving pre training by representing and predicting spans":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on contextual embeddings")
  Member "unsupervised pre training of image features on non curated data":
    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.CL(Computation and Language)