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 "expressing visual relationships via language"):
  Abstract: Describing images with text is a fundamental problem in vision-language research. Current studies in this domain mostly focus on single image captioning. However, in various real applications (e.g., image editing, difference interpretation, and retrieval), generating relational captions for two images, can also be very useful. This important problem has not been explored mostly due to lack of datasets and effective models. To push forward the research in this direction, we first introduce a new language-guided image editing dataset that contains a large number of real image pairs with corresponding editing instructions. We then propose a new relational speaker model based on an encoder-decoder architecture with static relational attention and sequential multi-head attention. We also extend the model with dynamic relational attention, which calculates visual alignment while decoding. Our models are evaluated on our newly collected and two public datasets consisting of image pairs annotated with relationship sentences. Experimental results, based on both automatic and human evaluation, demonstrate that our model outperforms all baselines and existing methods on all the datasets.

Includes members:
  Member "deep communicating agents for abstractive summarization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "what is this article about extreme summarization with topic aware convolutional neural networks")
  Member "learning to globally edit images with textual description":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "discriminability objective for training descriptive captions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reasoning visual dialogs with structural and partial observations")
  Member "learning to describe differences between pairs of similar images":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "a corpus for reasoning about natural language grounded in photographs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "break it down a question understanding benchmark")
  Member "learning to color from language":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tag2pix line art colorization using text tag with secat and changing loss")
  Member "pragmatically informative image captioning with character level reference":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "reinforced video captioning with entailment rewards":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "delving deeper into the decoder for video captioning")

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)