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 "multi task multi domain representation learning for sequence tagging"):
  Abstract: Representation learning with deep models have demonstrated success in a range of NLP. In this paper we consider its use in a multi-task multi-domain setting for sequence tagging by proposing a unified framework for learning across tasks and domains. Our model learns robust representations that yield better performance in this setting. We use shared CRFs and domain projections to allow the model to learn domain specific representations that can feed a single task specific CRF. We evaluate our model on two tasks -- Chinese word segmentation and named entity recognition -- and two domains -- news and social media -- and achieve state-of-the-art results for both social media tasks.

Includes members:
  Member "multi task learning for mental health using social media text":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi task learning for argumentation mining")
  Member "span based constituency parsing with a structure label system and provably optimal dynamic oracles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "disentangling adaptive gradient methods from learning rates")
  Member "end to end sequence labeling via bi directional lstm cnns crf":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secnlp a survey of embeddings in clinical natural language processing")
  Member "multi task cross lingual sequence tagging from scratch":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi task learning for argumentation mining")
  Member "improving named entity recognition for chinese social media with word segmentation representation learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "integrating boundary assembling into a dnn framework for named entity recognition in chinese social media text")
  Member "neural architectures for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "knowledge graphs")
  Member "classifying relations via long short term memory networks along shortest dependency path":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reflex flexible framework for relation extraction in multiple domains")
  Member "transition based dependency parsing with stack long short term memory":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "improving entity linking by modeling latent entity type information")

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)