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 "towards multimodal emotion recognition in german speech events in cars using transfer learning"):
  Abstract: The recognition of emotions by humans is a complex process which considers multiple interacting signals such as facial expressions and both prosody and semantic content of utterances. Commonly, research on automatic recognition of emotions is, with few exceptions, limited to one modality. We describe an in-car experiment for emotion recognition from speech interactions for three modalities: the audio signal of a spoken interaction, the visual signal of the driver's face, and the manually transcribed content of utterances of the driver. We use off-the-shelf tools for emotion detection in audio and face and compare that to a neural transfer learning approach for emotion recognition from text which utilizes existing resources from other domains. We see that transfer learning enables models based on out-of-domain corpora to perform well. This method contributes up to 10 percentage points in F1, with up to 76 micro-average F1 across the emotions joy, annoyance and insecurity. Our findings also indicate that off-the-shelf-tools analyzing face and audio are not ready yet for emotion detection in in-car speech interactions without further adjustments.

Includes members:
  Member "ntua slp at iest 2018 ensemble of neural transfer methods for implicit emotion classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "attention based conditioning methods for external knowledge integration")
  Member "learning word vectors for 157 languages":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "iest wassa 2018 implicit emotions shared task":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "po emo conceptualization annotation and modeling of aesthetic emotions in german and english poetry")
  Member "amobee at iest 2018 transfer learning from language models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "latent universal task specific bert")
  Member "dailydialog a manually labelled multi turn dialogue dataset":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "emotion intensities in tweets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "attentive convolutional neural network based speech emotion recognition a study on the impact of input features signal length and acted speech":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "similarity of speech emotion in different languages revealed by a neural network with attention")
  Member "distant supervision for emotion detection using facebook reactions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "you write like you eat stylistic variation as a predictor of social stratification")

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.CL(Computation and Language)