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 "knowledge guided text retrieval and reading for open domain question answering"):
  Abstract: This paper presents a general approach for open-domain question answering (QA) that models interactions between paragraphs using structural information from a knowledge base. We first describe how to construct a graph of passages from a large corpus, where the relations are either from the knowledge base or the internal structure of Wikipedia. We then introduce a reading comprehension model which takes this graph as an input, to better model relationships across pairs of paragraphs. This approach consistently outperforms competitive baselines in three open-domain QA datasets, WebQuestions, Natural Questions and TriviaQA, improving the pipeline-based state-of-the-art by 3--13%.

Includes members:
  Member "latent retrieval for weakly supervised open domain question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "pullnet open domain question answering with iterative retrieval on knowledge bases and text":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "compositional questions do not necessitate multi hop reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a framework for evaluation of machine reading comprehension gold standards")
  Member "a discrete hard em approach for weakly supervised question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "multi passage bert a globally normalized bert model for open domain question answering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning to retrieve reasoning paths over wikipedia graph for question answering")
  Member "a bert baseline for the natural questions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tydi qa a benchmark for information seeking question answering in typologically diverse languages")
  Member "multi step entity centric information retrieval for multi hop question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "knowledgeable reader enhancing cloze style reading comprehension with external commonsense knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a study of the tasks and models in machine reading comprehension")

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)