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 "ties temporal interaction embeddings for enhancing social media integrity at facebook"):
  Abstract: Since its inception, Facebook has become an integral part of the online social community. People rely on Facebook to make connections with others and build communities. As a result, it is paramount to protect the integrity of such a rapidly growing network in a fast and scalable manner. In this paper, we present our efforts to protect various social media entities at Facebook from people who try to abuse our platform. We present a novel Temporal Interaction EmbeddingS (TIES) model that is designed to capture rogue social interactions and flag them for further suitable actions. TIES is a supervised, deep learning, production ready model at Facebook-scale networks. Prior works on integrity problems are mostly focused on capturing either only static or certain dynamic features of social entities. In contrast, TIES can capture both these variant behaviors in a unified model owing to the recent strides made in the domains of graph embedding and deep sequential pattern learning. To show the real-world impact of TIES, we present a few applications especially for preventing spread of misinformation, fake account detection, and reducing ads payment risks in order to enhance the platform's integrity.

Includes members:
  Member "predicting dynamic embedding trajectory in temporal interaction networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning multivariate hawkes processes at scale")
  Member "a survey of the recent architectures of deep convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a precisely xtreme multi channel hybrid approach for roman urdu sentiment analysis")
  Member "pytorch biggraph a large scale graph embedding system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interpretable and fair comparison of link prediction or entity alignment methods with adjusted mean rank")
  Member "poised spotting twitter spam off the beaten paths":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting cyberbullying and cyberaggression in social media")
  Member "deep learning for hate speech detection in tweets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fog computing on constrained devices paving the way for the future iot")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "in a world that counts clustering and detecting fake social engagement at scale":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how impersonators exploit instagram to generate fake engagement")
  Member "a critical review of recurrent neural networks for sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "ten social dimensions of conversations and relationships")

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.AI(Artificial Intelligence)