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 "sub event detection from twitter streams as a sequence labeling problem"):
  Abstract: This paper introduces improved methods for sub-event detection in social media streams, by applying neural sequence models not only on the level of individual posts, but also directly on the stream level. Current approaches to identify sub-events within a given event, such as a goal during a soccer match, essentially do not exploit the sequential nature of social media streams. We address this shortcoming by framing the sub-event detection problem in social media streams as a sequence labeling task and adopt a neural sequence architecture that explicitly accounts for the chronological order of posts. Specifically, we (i) establish a neural baseline that outperforms a graph-based state-of-the-art method for binary sub-event detection (2.7% micro-F1 improvement), as well as (ii) demonstrate superiority of a recurrent neural network model on the posts sequence level for labeled sub-events (2.4% bin-level F1 improvement over non-sequential models).

Includes members:
  Member "joint entity recognition and relation extraction as a multi head selection problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deeper task specificity improves joint entity and relation extraction")
  Member "adversarial training for multi context joint entity and relation extraction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "span based joint entity and relation extraction with transformer pre training")
  Member "global normalization of convolutional neural networks for joint entity and relation classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "end to end named entity recognition and relation extraction using pre trained language models")
  Member "an attentive neural architecture for joint segmentation and parsing and its application to real estate ads":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint entity recognition and relation extraction as a multi head selection problem")
  Member "sub story detection in twitter with hierarchical dirichlet processes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "modeling islamist extremist communications on social media using contextual dimensions religion ideology and hate")
  Member "convolutional neural networks for sentence classification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "towards real time summarization of scheduled events from twitter streams":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "intweetive text summarization")
  Member "human as real time sensors of social and physical events a case study of twitter and sports games":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "smerc social media event response clustering using textual and temporal 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)