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 "on the computation of distances for probabilistic context free grammars"):
  Abstract: Probabilistic context-free grammars (PCFGs) are used to define distributions over strings, and are powerful modelling tools in a number of areas, including natural language processing, software engineering, model checking, bio-informatics, and pattern recognition. A common important question is that of comparing the distributions generated or modelled by these grammars: this is done through checking language equivalence and computing distances. Two PCFGs are language equivalent if every string has identical probability with both grammars. This also means that the distance (whichever norm is used) is null. It is known that the language equivalence problem is interreducible with that of multiple ambiguity for context-free grammars, a long-standing open question. In this work, we prove that computing distances corresponds to solving undecidable questions: this is the case for the L1, L2 norm, the variation distance and the Kullback-Leibler divergence. Two more results are less negative: 1. The most probable string can be computed, and, 2. The Chebyshev distance (where the distance between two distributions is the maximum difference of probabilities over all strings) is interreducible with the language equivalence problem.

Includes members:
  Member "on the total variation distance of labelled markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the metric based approximate minimization of markov chains")
  Member "bisimilarity of probabilistic pushdown automata":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lattice structures for bisimilar probabilistic automata")

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.FL(Formal Languages and Automata Theory)