human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "bi modal first impressions recognition using temporally ordered deep audio and stochastic visual features"
  Abstract: We propose a novel approach for First Impressions Recognition in terms of the Big Five personality-traits from short videos. The Big Five personality traits is a model to describe human personality using five broad categories: Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness. We train two bi-modal end-to-end deep neural network architectures using temporally ordered audio and novel stochastic visual features from few frames, without over-fitting. We empirically show that the trained models perform exceptionally well, even after training from a small sub-portions of inputs. Our method is evaluated in ChaLearn LAP 2016 Apparent Personality Analysis (APA) competition using ChaLearn LAP APA2016 dataset and achieved excellent performance.

Connected through hyperedge HE-1 (induced by source paper "robust regression via deep negative correlation learning"):
  with members:
    - "residual non local attention networks for image restoration"
    - "bag of tricks for image classification with convolutional neural networks"
    - "first impressions a survey on vision based apparent personality trait analysis"
    - "explaining first impressions modeling recognizing and explaining apparent personality from videos"
    - "residual dense network for image super resolution"
    - "image super resolution via dual state recurrent networks"
    - "switching convolutional neural network for crowd counting"
    - "decidenet counting varying density crowds through attention guided detection and density estimation"

Connected through hyperedge HE-2 (induced by source paper "multimodal video based apparent personality recognition using long short term memory and convolutional neural networks"):
  with members:
    - "deep contextualized word representations"
    - "universal sentence encoder"
    - "deep impression audiovisual deep residual networks for multimodal apparent personality trait recognition"
    - "identity mappings in deep residual networks"
    - "cnn architectures for large scale audio classification"
    - "modern physiognomy an investigation on predicting personality traits and intelligence from the human face"
    - "youtube 8m a large scale video classification benchmark"
    - "joint face detection and alignment using multitask cascaded convolutional networks"

Connected through hyperedge HE-3 (induced by source paper "recent trends in deep learning based personality detection"):
  with members:
    - "sentiment and sarcasm classification with multitask learning"
    - "investigating audio visual and text fusion methods for end to end automatic personality prediction"
    - "explaining first impressions modeling recognizing and explaining apparent personality from videos"
    - "a deeper look into sarcastic tweets using deep convolutional neural networks"
    - "mosi multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos"
    - "finding function in form compositional character models for open vocabulary word representation"
    - "deep residual learning for image recognition"
    - "pr2 a language independent unsupervised tool for personality recognition from text"

Connected through hyperedge HE-4 (induced by source paper "on the effect of observed subject biases in apparent personality analysis from audio visual signals"):
  with members:
    - "multimodal explanations justifying decisions and pointing to the evidence"
    - "investigating audio visual and text fusion methods for end to end automatic personality prediction"
    - "first impressions a survey on vision based apparent personality trait analysis"
    - "explaining first impressions modeling recognizing and explaining apparent personality from videos"
    - "scut fbp5500 a diverse benchmark dataset for multi paradigm facial beauty prediction"
    - "age progression regression by conditional adversarial autoencoder"
    - "heterogeneous face attribute estimation a deep multi task learning approach"
    - "deep impression audiovisual deep residual networks for multimodal apparent personality trait recognition"

Connected through hyperedge HE-5 (induced by source paper "towards universal end to end affect recognition from multilingual speech by convnets"):
  with members:
    - "towards empathetic human robot interactions"
    - "deep impression audiovisual deep residual networks for multimodal apparent personality trait recognition"
    - "fast and accurate deep network learning by exponential linear units elus"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-6 (induced by source paper "persemon a deep network for joint analysis of apparent personality emotion and their relationship"):
  with members:
    - "affectnet a database for facial expression valence and arousal computing in the wild"
    - "first impressions a survey on vision based apparent personality trait analysis"
    - "explaining first impressions modeling recognizing and explaining apparent personality from videos"
    - "sphereface deep hypersphere embedding for face recognition"
    - "facial affect estimation in the wild using deep residual and convolutional networks"
    - "emotion recognition in the wild using deep neural networks and bayesian classifiers"
    - "deep impression audiovisual deep residual networks for multimodal apparent personality trait recognition"
    - "temporal segment networks towards good practices for deep action recognition"

Connected through hyperedge HE-7 (induced by source paper "first impressions a survey on vision based apparent personality trait analysis"):
  with members:
    - "survey on emotional body gesture recognition"
    - "explaining first impressions modeling recognizing and explaining apparent personality from videos"
    - "semantics derived automatically from language corpora contain human like biases"
    - "deep impression audiovisual deep residual networks for multimodal apparent personality trait recognition"
    - "avec 2016 depression mood and emotion recognition workshop and challenge"
    - "action recognition with dynamic image networks"

Connected through hyperedge HE-8 (induced by source paper "investigating audio visual and text fusion methods for end to end automatic personality prediction"):
  with members:
    - "multimodal machine learning a survey and taxonomy"
    - "adam a method for stochastic optimization"
    - "very deep convolutional networks for large scale image recognition"

Question: Please tell me which class the center node 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.CV(Computer Vision and Pattern Recognition)