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 "multimodal local global ranking fusion for emotion recognition"):
  Abstract: Emotion recognition is a core research area at the intersection of artificial intelligence and human communication analysis. It is a significant technical challenge since humans display their emotions through complex idiosyncratic combinations of the language, visual and acoustic modalities. In contrast to traditional multimodal fusion techniques, we approach emotion recognition from both direct person-independent and relative person-dependent perspectives. The direct person-independent perspective follows the conventional emotion recognition approach which directly infers absolute emotion labels from observed multimodal features. The relative person-dependent perspective approaches emotion recognition in a relative manner by comparing partial video segments to determine if there was an increase or decrease in emotional intensity. Our proposed model integrates these direct and relative prediction perspectives by dividing the emotion recognition task into three easier subtasks. The first subtask involves a multimodal local ranking of relative emotion intensities between two short segments of a video. The second subtask uses local rankings to infer global relative emotion ranks with a Bayesian ranking algorithm. The third subtask incorporates both direct predictions from observed multimodal behaviors and relative emotion ranks from local-global rankings for final emotion prediction. Our approach displays excellent performance on an audio-visual emotion recognition benchmark and improves over other algorithms for multimodal fusion.

Includes members:
  Member "multimodal language analysis with recurrent multistage fusion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on emergent communication in competitive multi agent teams")
  Member "multimodal sentiment analysis with word level fusion and reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gated mechanism for attention based multimodal sentiment analysis")
  Member "multi attention recurrent network for human communication comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gated mechanism for attention based multimodal sentiment analysis")
  Member "efficient low rank multimodal fusion with modality specific factors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "h owan multi distorted image restoration with tensor 1x1 convolution")
  Member "seq2seq2sentiment multimodal sequence to sequence models for sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "found in translation learning robust joint representations by cyclic translations between modalities")
  Member "learning factorized multimodal representations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "robust multimodal brain tumor segmentation via feature disentanglement and gated fusion")
  Member "memory fusion network for multi view sequential learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "emotions don t lie a deepfake detection method using audio visual affective cues")
  Member "speech recognition with deep recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "centrality graph convolutional networks for skeleton based action recognition")

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)