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 "accurate and robust eye contact detection during everyday mobile device interactions"):
  Abstract: Quantification of human attention is key to several tasks in mobile human-computer interaction (HCI), such as predicting user interruptibility, estimating noticeability of user interface content, or measuring user engagement. Previous works to study mobile attentive behaviour required special-purpose eye tracking equipment or constrained users' mobility. We propose a novel method to sense and analyse visual attention on mobile devices during everyday interactions. We demonstrate the capabilities of our method on the sample task of eye contact detection that has recently attracted increasing research interest in mobile HCI. Our method builds on a state-of-the-art method for unsupervised eye contact detection and extends it to address challenges specific to mobile interactive scenarios. Through evaluation on two current datasets, we demonstrate significant performance improvements for eye contact detection across mobile devices, users, or environmental conditions. Moreover, we discuss how our method enables the calculation of additional attention metrics that, for the first time, enable researchers from different domains to study and quantify attention allocation during mobile interactions in the wild.

Includes members:
  Member "evaluation of appearance based methods and implications for gaze based applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "few shot adaptive gaze estimation")
  Member "forecasting user attention during everyday mobile interactions using device integrated and wearable sensors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "evaluation of appearance based methods and implications for gaze based applications")
  Member "light weight head pose invariant gaze tracking":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")
  Member "mpiigaze real world dataset and deep appearance based gaze estimation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an efficient method of training small models for regression problems with knowledge distillation")
  Member "eye tracking for everyone":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")
  Member "joint face detection and alignment using multitask cascaded convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "it s written all over your face full face appearance based gaze estimation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")
  Member "appearance based gaze estimation in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")

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.HC(Human-Computer Interaction)