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 "probing the need for visual context in multimodal machine translation"):
  Abstract: Current work on multimodal machine translation (MMT) has suggested that the visual modality is either unnecessary or only marginally beneficial. We posit that this is a consequence of the very simple, short and repetitive sentences used in the only available dataset for the task (Multi30K), rendering the source text sufficient as context. In the general case, however, we believe that it is possible to combine visual and textual information in order to ground translations. In this paper we probe the contribution of the visual modality to state-of-the-art MMT models by conducting a systematic analysis where we partially deprive the models from source-side textual context. Our results show that under limited textual context, models are capable of leveraging the visual input to generate better translations. This contradicts the current belief that MMT models disregard the visual modality because of either the quality of the image features or the way they are integrated into the model.

Includes members:
  Member "lium cvc submissions for wmt18 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "debiasing word embeddings improves multimodal machine translation")
  Member "cuni system for the wmt18 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "two headed monster and crossed co attention networks")
  Member "the memad submission to the wmt18 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on architectures for including visual information in neural language models for image description")
  Member "nmtpy a flexible toolkit for advanced neural machine translation systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "looking enhances listening recovering missing speech using images")
  Member "findings of the second shared task on multimodal machine translation and multilingual image description":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vatex a large scale high quality multilingual dataset for video and language research")
  Member "attention strategies for multi source sequence to sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "vatex a large scale high quality multilingual dataset for video and language research")
  Member "osu multimodal machine translation system report":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "vatex a large scale high quality multilingual dataset for video and language research")
  Member "lium cvc submissions for wmt17 multimodal translation task":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vatex a large scale high quality multilingual dataset for video and language research")

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)