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 "exploring hate speech detection in multimodal publications"):
  Abstract: In this work we target the problem of hate speech detection in multimodal publications formed by a text and an image. We gather and annotate a large scale dataset from Twitter, MMHS150K, and propose different models that jointly analyze textual and visual information for hate speech detection, comparing them with unimodal detection. We provide quantitative and qualitative results and analyze the challenges of the proposed task. We find that, even though images are useful for the hate speech detection task, current multimodal models cannot outperform models analyzing only text. We discuss why and open the field and the dataset for further research.

Includes members:
  Member "learning to learn from web data through deep semantic embeddings":
    also connected through other hyperedges:
      (none)
  Member "recurrent fusion network for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deconfounded image captioning a causal retrospect")
  Member "peer to peer hate hate speech instigators and their targets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a benchmark dataset for learning to intervene in online hate speech")
  Member "automated hate speech detection and the problem of offensive language":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "detecting hate speech in social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "offensive language identification in greek")
  Member "one step and two step classification for abusive language detection on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nlpr srpol at semeval 2019 task 6 and task 5 linguistically enhanced deep learning offensive sentence classifier")
  Member "improving text proposals for scene images with fully convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "selective style transfer for text")
  Member "a web of hate tackling hateful speech in online social spaces":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "temporal effects of unmoderated hate speech in gab")

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.CV(Computer Vision and Pattern Recognition)