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 "evaluation of appearance based methods and implications for gaze based applications"):
  Abstract: Appearance-based gaze estimation methods that only require an off-the-shelf camera have significantly improved but they are still not yet widely used in the human-computer interaction (HCI) community. This is partly because it remains unclear how they perform compared to model-based approaches as well as dominant, special-purpose eye tracking equipment. To address this limitation, we evaluate the performance of state-of-the-art appearance-based gaze estimation for interaction scenarios with and without personal calibration, indoors and outdoors, for different sensing distances, as well as for users with and without glasses. We discuss the obtained findings and their implications for the most important gaze-based applications, namely explicit eye input, attentive user interfaces, gaze-based user modelling, and passive eye monitoring. To democratise the use of appearance-based gaze estimation and interaction in HCI, we finally present OpenGaze (www.opengaze.org), the first software toolkit for appearance-based gaze estimation and interaction.

Includes members:
  Member "forecasting user attention during everyday mobile interactions using device integrated and wearable sensors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "accurate and robust eye contact detection during everyday mobile device interactions")
  Member "detecting low rapport during natural interactions in small groups from non verbal behaviour":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "emergent leadership detection across datasets")
  Member "learning to find eye region landmarks for remote gaze estimation in unconstrained settings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint iris segmentation and localization using deep multi task learning framework")
  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 "learning from simulated and unsupervised images through adversarial training":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "it s written all over your face full face appearance based gaze estimation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "geddnet a network for gaze estimation with dilation and decomposition")
  Member "rendering of eyes for eye shape registration and gaze estimation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "magiceyes a large scale eye gaze estimation dataset for mixed reality")
  Member "tabletgaze unconstrained appearance based gaze estimation in mobile tablets":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "unsupervised representation learning for gaze estimation")

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)