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 "tener adapting transformer encoder for named entity recognition"):
  Abstract: The Bidirectional long short-term memory networks (BiLSTM) have been widely used as an encoder in models solving the named entity recognition (NER) task. Recently, the Transformer is broadly adopted in various Natural Language Processing (NLP) tasks owing to its parallelism and advantageous performance. Nevertheless, the performance of the Transformer in NER is not as good as it is in other NLP tasks. In this paper, we propose TENER, a NER architecture adopting adapted Transformer Encoder to model the character-level features and word-level features. By incorporating the direction and relative distance aware attention and the un-scaled attention, we prove the Transformer-like encoder is just as effective for NER as other NLP tasks.

Includes members:
  Member "can ner convolutional attention network for chinese named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "self attention based bigru and capsule network for named entity recognition")
  Member "grn gated relation network to enhance convolutional neural network for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hierarchical contextualized representation for named entity recognition")
  Member "transformer xl attentive language models beyond a fixed length context":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on contextual embeddings")
  Member "sequence labeling a practical approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi scale self attention for text classification")
  Member "chinese ner using lattice lstm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "self attention based bigru and capsule network for named entity recognition")
  Member "self attention with relative position representations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "non autoregressive neural dialogue generation")
  Member "robust lexical features for improved neural network named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "attention based conditioning methods for external knowledge integration")
  Member "contextualized non local neural networks for sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "reinforcement learning based graph to sequence model for natural question generation")

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)