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 "a study on multimodal and interactive explanations for visual question answering"):
  Abstract: Explainability and interpretability of AI models is an essential factor affecting the safety of AI. While various explainable AI (XAI) approaches aim at mitigating the lack of transparency in deep networks, the evidence of the effectiveness of these approaches in improving usability, trust, and understanding of AI systems are still missing. We evaluate multimodal explanations in the setting of a Visual Question Answering (VQA) task, by asking users to predict the response accuracy of a VQA agent with and without explanations. We use between-subjects and within-subjects experiments to probe explanation effectiveness in terms of improving user prediction accuracy, confidence, and reliance, among other factors. The results indicate that the explanations help improve human prediction accuracy, especially in trials when the VQA system's answer is inaccurate. Furthermore, we introduce active attention, a novel method for evaluating causal attentional effects through intervention by editing attention maps. User explanation ratings are strongly correlated with human prediction accuracy and suggest the efficacy of these explanations in human-machine AI collaboration tasks.

Includes members:
  Member "generating natural language explanations for visual question answering using scene graphs and visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "natural language generation for non expert users")
  Member "grounding visual explanations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "explaining with counter visual attributes and examples")
  Member "multimodal explanations justifying decisions and pointing to the evidence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust explanations for visual question answering")
  Member "pythia v0 1 the winning entry to the vqa challenge 2018":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "in defense of grid features for visual question answering")
  Member "how do humans understand explanations from machine learning systems an evaluation of the human interpretability of explanation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "show ask attend and answer a strong baseline for visual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cq vqa visual question answering on categorized questions")
  Member "tips and tricks for visual question answering learnings from the 2017 challenge":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "in defense of grid features for visual question answering")
  Member "inception v4 inception resnet and the impact of residual connections on learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stem seg spatio temporal embeddings for instance segmentation in videos")

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.AI(Artificial Intelligence)