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 "efficient attention mechanism for handling all the interactions between many inputs with application to visual dialog"):
  Abstract: It has been a primary concern in recent studies of vision and language tasks to design an effective attention mechanism dealing with interactions between the two modalities. The Transformer has recently been extended and applied to several bi-modal tasks, yielding promising results. For visual dialog, it becomes necessary to consider interactions between three or more inputs, i.e., an image, a question, and a dialog history, or even its individual dialog components. In this paper, we present a neural architecture that can efficiently deal with all the interactions between many such inputs. It has a block structure similar to the Transformer and employs the same design of attention computation, whereas it has only a small number of parameters, yet has sufficient representational power for the purpose. Assuming a standard setting of visual dialog, a network built upon the proposed attention block has less than one-tenth of parameters as compared with its counterpart, a natural Transformer extension. We present its application to the visual dialog task. The experimental results validate the effectiveness of the proposed approach, showing improvements of the best NDCG score on the VisDial v1.0 dataset from 57.59 to 60.92 with a single model, from 64.47 to 66.53 with ensemble models, and even to 74.88 with additional finetuning.

Includes members:
  Member "lxmert learning cross modality encoder representations from transformers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "uniter learning universal image text representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "in defense of grid features for visual question answering")
  Member "reasoning visual dialogs with structural and partial observations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hierarchical human parsing with typed part relation reasoning")
  Member "making history matter history advantage sequence training for visual dialog":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "guessing state tracking for visual dialogue")
  Member "dual attention networks for visual reference resolution in visual dialog":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vision dialog navigation by exploring cross modal memory")
  Member "vilbert pretraining task agnostic visiolinguistic representations for vision and language tasks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bert can see out of the box on the cross modal transferability of text representations")
  Member "albert a lite bert for self supervised learning of language representations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "multi step reasoning via recurrent dual attention for visual dialog":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vision dialog navigation by exploring cross modal memory")

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)