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 "exploiting bert for end to end aspect based sentiment analysis"):
  Abstract: In this paper, we investigate the modeling power of contextualized embeddings from pre-trained language models, e.g. BERT, on the E2E-ABSA task. Specifically, we build a series of simple yet insightful neural baselines to deal with E2E-ABSA. The experimental results show that even with a simple linear classification layer, our BERT-based architecture can outperform state-of-the-art works. Besides, we also standardize the comparative study by consistently utilizing a hold-out validation dataset for model selection, which is largely ignored by previous works. Therefore, our work can serve as a BERT-based benchmark for E2E-ABSA.

Includes members:
  Member "syntax aware aspect level sentiment classification with graph attention networks":
    also connected through other hyperedges:
      (none)
  Member "fine tune bert for extractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "what is this article about extreme summarization with topic aware convolutional neural networks")
  Member "targeted sentiment classification with attentional encoder network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adversarial training for aspect based sentiment analysis with bert")
  Member "utilizing bert for aspect based sentiment analysis via constructing auxiliary sentence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "description based text classification with reinforcement learning")
  Member "open domain targeted sentiment analysis via span based extraction and classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a novel aspect guided deep transition model for aspect based sentiment analysis")
  Member "adapt or get left behind domain adaptation through bert language model finetuning for aspect target sentiment classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adversarial training for aspect based sentiment analysis with bert")
  Member "aspect based sentiment classification with aspect specific graph convolutional networks":
    also connected through other hyperedges:
      (none)
  Member "an interactive multi task learning network for end to end aspect based sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a novel aspect guided deep transition model for aspect based sentiment analysis")

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)