human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "pruning a bert based question answering model"
  Abstract: We investigate compressing a BERT-based question answering system by pruning parameters from the underlying BERT model. We start from models trained for SQuAD 2.0 and introduce gates that allow selected parts of transformers to be individually eliminated. Specifically, we investigate (1) reducing the number of attention heads in each transformer, (2) reducing the intermediate width of the feed-forward sublayer of each transformer, and (3) reducing the embedding dimension. We compare several approaches for determining the values of these gates. We find that a combination of pruning attention heads and the feed-forward layer almost doubles the decoding speed, with only a 1.5 f-point loss in accuracy.

Connected through hyperedge HE-1 (induced by source paper "power bert accelerating bert inference for classification tasks"):
  with members:
    - "are sixteen heads really better than one"
    - "biobert a pre trained biomedical language representation model for biomedical text mining"
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "adaptively sparse transformers"
    - "q bert hessian based ultra low precision quantization of bert"
    - "sparse sequence to sequence models"
    - "explicit sparse transformer concentrated attention through explicit selection"
    - "albert a lite bert for self supervised learning of language representations"

Question: Please tell me which class the center node 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)