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 "towards vqa models that can read"):
  Abstract: Studies have shown that a dominant class of questions asked by visually impaired users on images of their surroundings involves reading text in the image. But today's VQA models can not read! Our paper takes a first step towards addressing this problem. First, we introduce a new "TextVQA" dataset to facilitate progress on this important problem. Existing datasets either have a small proportion of questions about text (e.g., the VQA dataset) or are too small (e.g., the VizWiz dataset). TextVQA contains 45,336 questions on 28,408 images that require reasoning about text to answer. Second, we introduce a novel model architecture that reads text in the image, reasons about it in the context of the image and the question, and predicts an answer which might be a deduction based on the text and the image or composed of the strings found in the image. Consequently, we call our approach Look, Read, Reason & Answer (LoRRA). We show that LoRRA outperforms existing state-of-the-art VQA models on our TextVQA dataset. We find that the gap between human performance and machine performance is significantly larger on TextVQA than on VQA 2.0, suggesting that TextVQA is well-suited to benchmark progress along directions complementary to VQA 2.0.

Includes members:
  Member "bilinear attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "in defense of grid features for visual question answering")
  Member "learning to count objects in natural images for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "in defense of grid features for visual question answering")
  Member "pythia v0 1 the winning entry to the vqa challenge 2018":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "in defense of grid features for visual question answering")
  Member "vizwiz grand challenge answering visual questions from blind people":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "in defense of grid features for visual question answering")
  Member "disentangling language and knowledge in task oriented dialogs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "low resource knowledge grounded dialogue generation")
  Member "rosetta large scale system for text detection and recognition in images":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep multi modal sets")
  Member "dvqa understanding data visualizations via question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "manymodalqa modality disambiguation and qa over diverse inputs")
  Member "figureqa an annotated figure dataset for visual reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "plotqa reasoning over scientific plots")

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)