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 "sequence to sequence speech recognition with time depth separable convolutions"):
  Abstract: We propose a fully convolutional sequence-to-sequence encoder architecture with a simple and efficient decoder. Our model improves WER on LibriSpeech while being an order of magnitude more efficient than a strong RNN baseline. Key to our approach is a time-depth separable convolution block which dramatically reduces the number of parameters in the model while keeping the receptive field large. We also give a stable and efficient beam search inference procedure which allows us to effectively integrate a language model. Coupled with a convolutional language model, our time-depth separable convolution architecture improves by more than 22% relative WER over the best previously reported sequence-to-sequence results on the noisy LibriSpeech test set.

Includes members:
  Member "pay less attention with lightweight and dynamic convolutions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on feature normalization and data augmentation")
  Member "sentencepiece a simple and language independent subword tokenizer and detokenizer for neural text processing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multilingual denoising pre training for neural machine translation")
  Member "the capio 2017 conversational speech recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who needs words lexicon free speech recognition")
  Member "fully convolutional speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "scaling up online speech recognition using convnets")
  Member "subword regularization improving neural network translation models with multiple subword candidates":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fastai a layered api for deep learning")
  Member "wav2letter the fastest open source speech recognition system":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "self supervised speech recognition via local prior matching")
  Member "exploring the limits of weakly supervised pretraining":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "improved training of end to end attention models for speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "scaling up online speech recognition using convnets")

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)