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: "arsenal automatic requirements specification extraction from natural language"
  Abstract: Requirements are informal and semi-formal descriptions of the expected behavior of a complex system from the viewpoints of its stakeholders (customers, users, operators, designers, and engineers). However, for the purpose of design, testing, and verification for critical systems, we can transform requirements into formal models that can be analyzed automatically. ARSENAL is a framework and methodology for systematically transforming natural language (NL) requirements into analyzable formal models and logic specifications. These models can be analyzed for consistency and implementability. The ARSENAL methodology is specialized to individual domains, but the approach is general enough to be adapted to new domains.

Connected through hyperedge HE-1 (induced by source paper "towards a framework for certification of reliable autonomous systems"):
  with members:
    - "formal specification and verification of autonomous robotic systems a survey"
    - "stream runtime monitoring on uas"
    - "robotics and integrated formal methods necessity meets opportunity"
    - "towards moral autonomous systems"

Connected through hyperedge HE-2 (induced by source paper "a methodology for automating assurance case generation"):
  with members:
    - "augmenting learning components for safety in resource constrained autonomous robots"
    - "analysis and extension of the evidential reasoning algorithm for multiple attribute decision analysis with uncertainty"
    - "resolute an assurance case language for architecture models"

Connected through hyperedge HE-3 (induced by source paper "validating an approach to formalize use cases with ontologies"):
  with members:
    - "application of ontologies in identifying requirements patterns in use cases"

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.CL(Computation and Language)