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 "what s missing a knowledge gap guided approach for multi hop question answering"):
  Abstract: Multi-hop textual question answering requires combining information from multiple sentences. We focus on a natural setting where, unlike typical reading comprehension, only partial information is provided with each question. The model must retrieve and use additional knowledge to correctly answer the question. To tackle this challenge, we develop a novel approach that explicitly identifies the knowledge gap between a key span in the provided knowledge and the answer choices. The model, GapQA, learns to fill this gap by determining the relationship between the span and an answer choice, based on retrieved knowledge targeting this gap. We propose jointly training a model to simultaneously fill this knowledge gap and compose it with the provided partial knowledge. On the OpenBookQA dataset, given partial knowledge, explicitly identifying what's missing substantially outperforms previous approaches.

Includes members:
  Member "improving question answering with external knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sirenless reveal the intention behind news")
  Member "understanding dataset design choices for multi hop reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a framework for evaluation of machine reading comprehension gold standards")
  Member "careful selection of knowledge to solve open book question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "can a suit of armor conduct electricity a new dataset for open book question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "knowledgeable reader enhancing cloze style reading comprehension with external commonsense knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "dynamic integration of background knowledge in neural nlu systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "hotpotqa a dataset for diverse explainable multi hop question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "worldtree a corpus of explanation graphs for elementary science questions supporting multi hop inference":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transformers as soft reasoners over language")

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)