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 "neural mention detection"):
  Abstract: Mention detection is an important aspect of the annotation task and interpretation process for applications such as coreference resolution. In this work, we propose and compare three neural network-based approaches to mention detection. The first approach is based on the mention detection part of a state-of-the-art coreference resolution system; the second uses ELMo embeddings together with a bidirectional LSTM and a biaffine classifier; the third approach uses the recently introduced BERT model. Our best model (using a biaffine classifier) achieved gains of up to 1.8 percentage points on mention recall when compared with a strong baseline in a HIGH RECALL setting. The same model achieved improvements of up to 5.3 and 6.5 p.p. when compared with the best-reported mention detection F1 on thevCONLL and CRAC data sets respectively in a HIGH F1 setting. We further evaluated our models on coreference resolution by using mentions predicted by our best model in the start-of-the-art coreference systems. The enhanced model achieved absolute improvements of up to 1.7 and 0.7 p.p. when compared with the best pipeline system and the state-of-the-art end-to-end system respectively.

Includes members:
  Member "neural coreference resolution with deep biaffine attention by joint mention detection and mention clustering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coreference resolution as query based span prediction")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "higher order coreference resolution with coarse to fine inference":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multiplex word embeddings for selectional preference acquisition")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "end to end neural coreference resolution":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "domain independent extraction of scientific concepts from research articles")
  Member "improving coreference resolution by learning entity level distributed representations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi task learning based neural bridging reference resolution")
  Member "deep biaffine attention for neural dependency parsing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "lost in embedding space explaining cross lingual task performance with eigenvalue divergence")
  Member "learning global features for coreference resolution":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi task learning based neural bridging reference resolution")

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)