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 "univse robust visual semantic embeddings via structured semantic representations"):
  Abstract: We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts. The space unifies the concepts at different levels, including objects, attributes, relations, and full scenes. A contrastive learning approach is proposed for the fine-grained alignment from only image-caption pairs. Moreover, we present an effective approach for enforcing the coverage of semantic components that appear in the sentence. We demonstrate the robustness of Unified VSE in defending text-domain adversarial attacks on cross-modal retrieval tasks. Such robustness also empowers the use of visual cues to resolve word dependencies in novel sentences.

Includes members:
  Member "finding beans in burgers deep semantic visual embedding with localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mhsan multi head self attention network for visual semantic embedding")
  Member "learning visually grounded semantics from contrastive adversarial samples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the neuro symbolic concept learner interpreting scenes words and sentences from natural supervision")
  Member "long short term memory as a dynamically computed element wise weighted sum":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fundamentals of recurrent neural network rnn and long short term memory lstm network")
  Member "image generation from scene graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "pt2pc learning to generate 3d point cloud shapes from part tree conditions")
  Member "foil it find one mismatch between image and language caption":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "challenges and prospects in vision and language research")
  Member "vse improving visual semantic embeddings with hard negatives":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adversarial ranking attack and defense")
  Member "weakly supervised visual grounding of phrases with linguistic structures":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "incorporating visual semantics into sentence representations within a grounded space")
  Member "a structured self attentive sentence embedding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "high order paired aspp networks for semantic segmenation")

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)