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 "a joint model for multimodal document quality assessment"):
  Abstract: The quality of a document is affected by various factors, including grammaticality, readability, stylistics, and expertise depth, making the task of document quality assessment a complex one. In this paper, we explore this task in the context of assessing the quality of Wikipedia articles and academic papers. Observing that the visual rendering of a document can capture implicit quality indicators that are not present in the document text --- such as images, font choices, and visual layout --- we propose a joint model that combines the text content with a visual rendering of the document for document quality assessment. Experimental results over two datasets reveal that textual and visual features are complementary, achieving state-of-the-art results.

Includes members:
  Member "grad cam visual explanations from deep networks via gradient based localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "machine translation evaluation meets community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semeval 2017 task 3 community question answering")
  Member "a dataset of peer reviews peerread collection insights and nlp applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "textual analysis of artificial intelligence manuscripts reveals features associated with peer review outcome")
  Member "deep paper gestalt":
    also connected through other hyperedges:
      (none)
  Member "automatic academic paper rating based on modularized hierarchical convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "categorical metadata representation for customized text classification")
  Member "skipflow incorporating neural coherence features for end to end automatic text scoring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "question answering as an automatic evaluation metric for news article summarization")
  Member "automatic text scoring using neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "detection and mitigation of bias in ted talk ratings")
  Member "xception deep learning with depthwise separable convolutions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")

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)