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 "visual interaction with deep learning models through collaborative semantic inference"):
  Abstract: Automation of tasks can have critical consequences when humans lose agency over decision processes. Deep learning models are particularly susceptible since current black-box approaches lack explainable reasoning. We argue that both the visual interface and model structure of deep learning systems need to take into account interaction design. We propose a framework of collaborative semantic inference (CSI) for the co-design of interactions and models to enable visual collaboration between humans and algorithms. The approach exposes the intermediate reasoning process of models which allows semantic interactions with the visual metaphors of a problem, which means that a user can both understand and control parts of the model reasoning process. We demonstrate the feasibility of CSI with a co-designed case study of a document summarization system.

Includes members:
  Member "on human predictions with explanations and predictions of machine learning models a case study on deception detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "retainvis visual analytics with interpretable and interactive recurrent neural networks on electronic medical records":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "explainer a visual analytics framework for interactive and explainable machine learning")
  Member "semantic image synthesis with spatially adaptive normalization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gan compression efficient architectures for interactive conditional gans")
  Member "improving fairness in machine learning systems what do industry practitioners need":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "algorithmic fairness")
  Member "a tutorial on deep latent variable models of natural language":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "paraphrase generation with latent bag of words")
  Member "visual analytics in deep learning an interrogative survey for the next frontiers":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "explainer a visual analytics framework for interactive and explainable machine learning")
  Member "bottom up abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "minilm deep self attention distillation for task agnostic compression of pre trained transformers")
  Member "what is one grain of sand in the desert analyzing individual neurons in deep nlp models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the linguistic representational power of neural machine translation models")

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)