human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "oreo detection of clones in the twilight zone"
  Abstract: Source code clones are categorized into four types of increasing difficulty of detection, ranging from purely textual (Type-1) to purely semantic (Type-4). Most clone detectors reported in the literature work well up to Type-3, which accounts for syntactic differences. In between Type-3 and Type-4, however, there lies a spectrum of clones that, although still exhibiting some syntactic similarities, are extremely hard to detect – the Twilight Zone. Most clone detectors reported in the literature fail to operate in this zone. We present Oreo, a novel approach to source code clone detection that not only detects Type-1 to Type-3 clones accurately, but is also capable of detecting harder-to-detect clones in the Twilight Zone. Oreo is built using a combination of machine learning, information retrieval, and software metrics. We evaluate the recall of Oreo on BigCloneBench, and perform manual evaluation for precision. Oreo has both high recall and precision. More importantly, it pushes the boundary in detection of clones with moderate to weak syntactic similarity in a scalable manner

Connected through hyperedge HE-1 (induced by source paper "detecting code clones with graph neural networkand flow augmented abstract syntax tree"):
  with members:
    - "fast graph representation learning with pytorch geometric"
    - "graph matching networks for learning the similarity of graph structured objects"
    - "graph neural networks a review of methods and applications"
    - "convolutional neural networks over control flow graphs for software defect prediction"
    - "generative code modeling with graphs"
    - "neural message passing for quantum chemistry"
    - "learning to represent programs with graphs"
    - "gated graph sequence neural networks"

Connected through hyperedge HE-2 (induced by source paper "what you see is what it means semantic representation learning of code based on visualization and transfer learning"):
  with members:
    - "code2vec learning distributed representations of code"
    - "neural code comprehension a learnable representation of code semantics"
    - "the adverse effects of code duplication in machine learning models of code"
    - "vuldeepecker a deep learning based system for vulnerability detection"
    - "code2seq generating sequences from structured representations of code"
    - "look listen and learn"
    - "deep residual learning for image recognition"
    - "convolutional neural networks over tree structures for programming language processing"

Connected through hyperedge HE-3 (induced by source paper "an empirical study of c vulnerabilities in crowd sourced code examples"):
  with members:
    - "toxic code snippets on stack overflow"
    - "how reliable is the crowdsourced knowledge of security implementation"
    - "sotorrent reconstructing and analyzing the evolution of stack overflow posts"
    - "gistable evaluating the executability of python code snippets on github"
    - "sotorrent studying the origin evolution and usage of stack overflow code snippets"
    - "secure coding practices in java challenges and vulnerabilities"
    - "stack overflow considered harmful the impact of copy paste on android application security"
    - "leveraging flawed tutorials for seeding large scale web vulnerability discovery"

Connected through hyperedge HE-4 (induced by source paper "learning semantic vector representations of source code via a siamese neural network"):
  with members:
    - "code2vec learning distributed representations of code"
    - "code vectors understanding programs through embedded abstracted symbolic traces"
    - "a deep tree based model for software defect prediction"
    - "attention is all you need"
    - "learning python code suggestion with a sparse pointer network"
    - "facenet a unified embedding for face recognition and clustering"
    - "adam a method for stochastic optimization"
    - "tbcnn a tree based convolutional neural network for programming language processing"

Connected through hyperedge HE-5 (induced by source paper "aroma code recommendation via structural code search"):
  with members:
    - "sourcerercc scaling code clone detection to big code"
    - "swim synthesizing what i mean code search and idiomatic snippet synthesis"
    - "learning api usages from bytecode a statistical approach"

Connected through hyperedge HE-6 (induced by source paper "lvmapper a large variance clone detector using sequencing alignment approach"):
  with members:
    - "sourcerercc scaling code clone detection to big code"

Connected through hyperedge HE-7 (induced by source paper "towards automating precision studies of clone detectors"):
  with members:
    - "sourcerercc scaling code clone detection to big code"

Question: Please tell me which class the center node 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.SE(Software Engineering)