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 "dependent gated reading for cloze style question answering"):
  Abstract: We present a novel deep learning architecture to address the cloze-style question answering task. Existing approaches employ reading mechanisms that do not fully exploit the interdependency between the document and the query. In this paper, we propose a novel \emph{dependent gated reading} bidirectional GRU network (DGR) to efficiently model the relationship between the document and the query during encoding and decision making. Our evaluation shows that DGR obtains highly competitive performance on well-known machine comprehension benchmarks such as the Children's Book Test (CBT-NE and CBT-CN) and Who DiD What (WDW, Strict and Relaxed). Finally, we extensively analyze and validate our model by ablation and attention studies.

Includes members:
  Member "a thorough examination of the cnn daily mail reading comprehension task":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "tweet2vec character based distributed representations for social media":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "maskdga a black box evasion technique against dga classifiers and adversarial defenses")
  Member "dataset and neural recurrent sequence labeling model for open domain factoid question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "investigating prior knowledge for challenging chinese machine reading comprehension")
  Member "text understanding with the attention sum reader network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "retrospective reader for machine reading comprehension")
  Member "iterative alternating neural attention for machine reading":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi step reasoning via recurrent dual attention for visual dialog")
  Member "who did what a large scale person centered cloze dataset":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning cross context entity representations from text")
  Member "natural language comprehension with the epireader":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "saliency learning teaching the model where to pay attention")
  Member "gated attention readers for text comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a pilot study on multiple choice machine reading comprehension for vietnamese texts")

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)