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 "combining pattern based crfs and weighted context free grammars"):
  Abstract: We consider two models for the sequence labeling (tagging) problem. The first one is a {\em Pattern-Based Conditional Random Field }(\PB), in which the energy of a string (chain labeling) $x=x_1\ldots x_n\in D^n$ is a sum of terms over intervals $[i,j]$ where each term is non-zero only if the substring $x_i\ldots x_j$ equals a prespecified word $w\in \Lambda$. The second model is a {\em Weighted Context-Free Grammar }(\WCFG) frequently used for natural language processing. \PB and \WCFG encode local and non-local interactions respectively, and thus can be viewed as complementary. #R##N#We propose a {\em Grammatical Pattern-Based CRF model }(\GPB) that combines the two in a natural way. We argue that it has certain advantages over existing approaches such as the {\em Hybrid model} of Bened{\'i} and Sanchez that combines {\em $\mbox{$N$-grams}$} and \WCFGs. The focus of this paper is to analyze the complexity of inference tasks in a \GPB such as computing MAP. We present a polynomial-time algorithm for general \GPBs and a faster version for a special case that we call {\em Interaction Grammars}.

Includes members:
  Member "inference algorithms for pattern based crfs on sequence data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "patterns versus characters in subword aware neural language modeling")
  Member "the weighted cfg constraint":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "circuit complexity and decompositions of global constraints")
  Member "all pairs shortest paths using bridging sets and rectangular matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")

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)