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 "evidence sentence extraction for machine reading comprehension"):
  Abstract: Remarkable success has been achieved in the last few years on some limited machine reading comprehension (MRC) tasks. However, it is still difficult to interpret the predictions of existing MRC models. In this paper, we focus on extracting evidence sentences that can explain or support the answers of multiple-choice MRC tasks, where the majority of answer options cannot be directly extracted from reference documents. #R##N#Due to the lack of ground truth evidence sentence labels in most cases, we apply distant supervision to generate imperfect labels and then use them to train an evidence sentence extractor. To denoise the noisy labels, we apply a recently proposed deep probabilistic logic learning framework to incorporate both sentence-level and cross-sentence linguistic indicators for indirect supervision. We feed the extracted evidence sentences into existing MRC models and evaluate the end-to-end performance on three challenging multiple-choice MRC datasets: MultiRC, RACE, and DREAM, achieving comparable or better performance than the same models that take as input the full reference document. To the best of our knowledge, this is the first work extracting evidence sentences for multiple-choice MRC.

Includes members:
  Member "dream a challenge dataset and models for dialogue based reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reclor a reading comprehension dataset requiring logical reasoning")
  Member "training a ranking function for open domain question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dc bert decoupling question and document for efficient contextual encoding")
  Member "ukp athene multi sentence textual entailment for claim verification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "answering while summarizing multi task learning for multi hop qa with evidence extraction")
  Member "glue a multi task benchmark and analysis platform for natural language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "neural models for reasoning over multiple mentions using coreference":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "know what you don t know unanswerable questions for squad":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "description based text classification with reinforcement learning")
  Member "coqa a conversational question answering challenge":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on contextual embeddings")
  Member "deep probabilistic logic a unifying framework for indirect supervision":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "augmenting neural networks with first order logic")

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)