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 "conversation modeling on reddit using a graph structured lstm"):
  Abstract: This paper presents a novel approach for modeling threaded discussions on social media using a graph-structured bidirectional LSTM which represents both hierarchical and temporal conversation structure. In experiments with a task of predicting popularity of comments in Reddit discussions, the proposed model outperforms a node-independent architecture for different sets of input features. Analyses show a benefit to the model over the full course of the discussion, improving detection in both early and late stages. Further, the use of language cues with the bidirectional tree state updates helps with identifying controversial comments.

Includes members:
  Member "learning latent local conversation modes for predicting community endorsement in online discussions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the anatomy of reddit an overview of academic research")
  Member "deep reinforcement learning with a combinatorial action space for predicting popular reddit threads":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weakly supervised video summarization by hierarchical reinforcement learning")
  Member "recurrent neural network grammars":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hierarchical character embeddings learning phonological and semantic representations in languages of logographic origin using recursive neural networks")
  Member "theano a python framework for fast computation of mathematical expressions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the deep learning compiler a comprehensive survey")
  Member "compositional distributional semantics with long short term memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "structure tree lstm structure aware attentional document encoders")
  Member "improved semantic representations from tree structured long short term memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unbiased scene graph generation from biased training")
  Member "top down tree long short term memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hierarchical character embeddings learning phonological and semantic representations in languages of logographic origin using recursive neural networks")
  Member "seismic a self exciting point process model for predicting tweet popularity":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "inf vae a variational autoencoder framework to integrate homophily and influence in diffusion prediction")

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)