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 "attending to characters in neural sequence labeling models"):
  Abstract: Sequence labeling architectures use word embeddings for capturing similarity, but suffer when handling previously unseen or rare words. We investigate character-level extensions to such models and propose a novel architecture for combining alternative word representations. By using an attention mechanism, the model is able to dynamically decide how much information to use from a word- or character-level component. We evaluated different architectures on a range of sequence labeling datasets, and character-level extensions were found to improve performance on every benchmark. In addition, the proposed attention-based architecture delivered the best results even with a smaller number of trainable parameters.

Includes members:
  Member "a joint model for word embedding and word morphology":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "authorship attribution in bangla literature using character level cnn")
  Member "compositional sequence labeling models for error detection in learner writing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linguistic knowledge and transferability of contextual representations")
  Member "gated word character recurrent language model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gating mechanisms for combining character and word level word representations an empirical study")
  Member "neural architectures for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowledge graphs")
  Member "character based neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using interlinear glosses as pivot in low resource multilingual machine translation")
  Member "finding function in form compositional character models for open vocabulary word representation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hierarchical character embeddings learning phonological and semantic representations in languages of logographic origin using recursive neural networks")
  Member "improved transition based parsing by modeling characters instead of words with lstms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transition based dependency parsing using perceptron learner")
  Member "bidirectional lstm crf models for sequence tagging":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dense dilated convolutions merging network for land cover classification")

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)