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 "a novel task oriented text corpus in silent speech recognition and its natural language generation construction method"):
  Abstract: Millions of people with severe speech disorders around the world may regain their communication capabilities through techniques of silent speech recognition (SSR). Using electroencephalography (EEG) as a biomarker for speech decoding has been popular for SSR. However, the lack of SSR text corpus has impeded the development of this technique. Here, we construct a novel task-oriented text corpus, which is utilized in the field of SSR. In the process of construction, we propose a task-oriented hybrid construction method based on natural language generation algorithm. The algorithm focuses on the strategy of data-to-text generation, and has two advantages including linguistic quality and high diversity. These two advantages use template-based method and deep neural networks respectively. In an SSR experiment with the generated text corpus, analysis results show that the performance of our hybrid construction method outperforms the pure method such as template-based natural language generation or neural natural language generation models.

Includes members:
  Member "bert for joint intent classification and slot filling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rapid adaptation of bert for information extraction on domain specific business documents")
  Member "bert has a mouth and it must speak bert as a markov random field language model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bert as a teacher contextual embeddings for sequence level reward")
  Member "a context aware citation recommendation model with bert and graph convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bertscore evaluating text generation with bert")
  Member "a bert baseline for the natural questions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tydi qa a benchmark for information seeking question answering in typologically diverse languages")
  Member "speech recognition with no speech or with noisy speech":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "continuous speech recognition using eeg and video")
  Member "bottom up abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "minilm deep self attention distillation for task agnostic compression of pre trained transformers")
  Member "sequence to sequence models for data to text natural language generation word vs character based processing and output diversity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "evaluating the state of the art of end to end natural language generation the e2e nlg challenge")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)