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 "unsupervised discovery of multimodal links in multi image multi sentence documents"):
  Abstract: Images and text co-occur constantly on the web, but explicit links between images and sentences (or other intra-document textual units) are often not present. We present algorithms that discover image-sentence relationships without relying on explicit multimodal annotation in training. We experiment on seven datasets of varying difficulty, ranging from documents consisting of groups of images captioned post hoc by crowdworkers to naturally-occurring user-generated multimodal documents. We find that a structured training objective based on identifying whether collections of images and sentences co-occur in documents can suffice to predict links between specific sentences and specific images within the same document at test time.

Includes members:
  Member "align2ground weakly supervised phrase grounding guided by image caption alignment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scanrefer 3d object localization in rgb d scans using natural language")
  Member "dynamic multimodal instance segmentation guided by natural language queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi task collaborative network for joint referring expression comprehension and segmentation")
  Member "recipeqa a challenge dataset for multimodal comprehension of cooking recipes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "manymodalqa modality disambiguation and qa over diverse inputs")
  Member "quantifying the visual concreteness of words and topics in multimodal datasets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "visually grounded neural syntax acquisition")
  Member "exploring the limits of weakly supervised pretraining":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "learning transferable architectures for scalable image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "meta learning curiosity algorithms")
  Member "weakly supervised learning of visual relations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "unbiased scene graph generation via rich and fair semantic extraction")
  Member "segmentation from natural language expressions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hierarchical human parsing with typed part relation reasoning")

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)