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 "cops ref a new dataset and task on compositional referring expression comprehension"):
  Abstract: Referring expression comprehension (REF) aims at identifying a particular object in a scene by a natural language expression. It requires joint reasoning over the textual and visual domains to solve the problem. Some popular referring expression datasets, however, fail to provide an ideal test bed for evaluating the reasoning ability of the models, mainly because 1) their expressions typically describe only some simple distinctive properties of the object and 2) their images contain limited distracting information. To bridge the gap, we propose a new dataset for visual reasoning in context of referring expression comprehension with two main features. First, we design a novel expression engine rendering various reasoning logics that can be flexibly combined with rich visual properties to generate expressions with varying compositionality. Second, to better exploit the full reasoning chain embodied in an expression, we propose a new test setting by adding additional distracting images containing objects sharing similar properties with the referent, thus minimising the success rate of reasoning-free cross-domain alignment. We evaluate several state-of-the-art REF models, but find none of them can achieve promising performance. A proposed modular hard mining strategy performs the best but still leaves substantial room for improvement. We hope this new dataset and task can serve as a benchmark for deeper visual reasoning analysis and foster the research on referring expression comprehension.

Includes members:
  Member "improving referring expression grounding with cross modal attention guided erasing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "giving commands to a self driving car a multimodal reasoner for visual grounding")
  Member "visual semantic reasoning for image text matching":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive offline quintuplet loss for image text matching")
  Member "clevr ref diagnosing visual reasoning with referring expressions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi task learning by a top down control network")
  Member "binary image selection bison interpretable evaluation of visual grounding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cooperative image captioning")
  Member "cross modal self attention network for referring image segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi task collaborative network for joint referring expression comprehension and segmentation")
  Member "neural sequential phrase grounding seqground":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scanrefer 3d object localization in rgb d scans using natural language")
  Member "cross modal relationship inference for grounding referring expressions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relationship embedded representation learning for grounding referring expressions")
  Member "neighbourhood watch referring expression comprehension via language guided graph attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi task collaborative network for joint referring expression comprehension and segmentation")

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)