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: "multivariate fine grained complexity of longest common subsequence"
  Abstract: We revisit the classic combinatorial pattern matching problem of finding a longest common subsequence (LCS). For strings x and y of length n, a textbook algorithm solves LCS in time O(n2), but although much effort has been spent, no O(n2−ϵ)-time algorithm is known. Recent work indeed shows that such an algorithm would refute the Strong Exponential Time Hypothesis (SETH) [Abboud, Backurs, Vassilevska Williams FOCS'15; Bringmann, Kunnemann FOCS'15].   Despite the quadratic-time barrier, for over 40 years an enduring scientific interest continued to produce fast algorithms for LCS and its variations. Particular attention was put into identifying and exploiting input parameters that yield strongly subquadratic time algorithms for special cases of interest, e.g., differential file comparison. This line of research was successfully pursued until 1990, at which time significant improvements came to a halt. In this paper, using the lens of fine-grained complexity, our goal is to (1) justify the lack of further improvements and (2) determine whether some special cases of LCS admit faster algorithms than currently known.   To this end, we provide a systematic study of the multivariate complexity of LCS, taking into account all parameters previously discussed in the literature: the input size n := max{|x|, |y|}, the length of the shorter string m := min{|x|, |y|}, the length L of an LCS of x and y, the numbers of deletions Δ := m − L and Δ := n − L, the alphabet size, as well as the numbers of matching pairs M and dominant pairs d. For any class of instances defined by fixing each parameter individually to a polynomial in terms of the input size, we prove a SETH-based lower bound matching one of three known algorithms (up to lower order factors of the form no(1)). Specifically, we determine the optimal running time for LCS under SETH as (n + min{d, ΔΔ, Δm})1±o(1). Polynomial improvements over this running time must necessarily refute SETH or exploit novel input parameters. We establish the same lower bound for any constant alphabet of size at least 3. For binary alphabet, we show a SETH-based lower bound of (n + min{d, ΔΔ, ΔM/n})1−o(1) and, motivated by difficulties to improve this lower bound, we design an O(n+ΔM/n)-time algorithm, yielding again a matching bound.   We feel that our systematic approach yields a comprehensive perspective on the well-studied multivariate complexity of LCS, and we hope to inspire similar studies of multivariate complexity landscapes for further polynomial-time problems.

Connected through hyperedge HE-1 (induced by source paper "streaming with oracle new streaming algorithms for edit distance and lcs"):
  with members:
    - "approximating lcs in linear time beating the sqrt n barrier"
    - "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation"
    - "sublinear algorithms for gap edit distance"
    - "reducing approximate longest common subsequence to approximate edit distance"
    - "constant factor approximation of near linear edit distance in near linear time"
    - "constant factor approximations to edit distance on far input pairs in nearly linear time"
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "on estimating edit distance alignment dimension reduction and embeddings"

Connected through hyperedge HE-2 (induced by source paper "scattered factor universality of words"):
  with members:
    - "k spectra of weakly c balanced words"
    - "languages ordered by the subword order"
    - "computing the k binomial complexity of the thue morse word"
    - "testing simon s congruence"
    - "decidability complexity and expressiveness of first order logic over the subword ordering"
    - "complexity of universality and related problems for partially ordered nfas"
    - "the complexity of downward closure comparisons"
    - "on the index of simon s congruence for piecewise testability"

Connected through hyperedge HE-3 (induced by source paper "complexity of combinatorial matrix completion with diameter constraints"):
  with members:
    - "on clustering incomplete data"
    - "exploiting hidden structure in selecting dimensions that distinguish vectors"

Connected through hyperedge HE-4 (induced by source paper "near linear time insertion deletion codes and 1 e approximating edit distance via indexing"):
  with members:
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "approximating edit distance in truly subquadratic time quantum and mapreduce"
    - "synchronization strings list decoding for insertions and deletions"
    - "synchronization strings channel simulations and interactive coding for insertions and deletions"
    - "synchronization strings explicit constructions local decoding and applications"
    - "synchronization strings efficient and fast deterministic constructions over small alphabets"
    - "synchronization strings codes for insertions and deletions approaching the singleton bound"
    - "efficiently decodable insertion deletion codes for high noise and high rate regimes"

Connected through hyperedge HE-5 (induced by source paper "a sub quadratic algorithm for the longest common increasing subsequence problem"):
  with members:
    - "tighter connections between formula sat and shaving logs"
    - "why is it hard to beat o n 2 for longest common weakly increasing subsequence"
    - "tight conditional lower bounds for longest common increasing subsequence"
    - "faster online matrix vector multiplication"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "quadratic time hardness of lcs and other sequence similarity measures"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-6 (induced by source paper "parameterized fine grained reductions"):
  with members:
    - "an equivalence class for orthogonal vectors"
    - "more consequences of falsifying seth and the orthogonal vectors conjecture"
    - "tighter connections between formula sat and shaving logs"
    - "the orthogonal vectors conjecture for branching programs and formulas"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "approximation and fixed parameter subquadratic algorithms for radius and diameter"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "confronting intractability via parameters"

Connected through hyperedge HE-7 (induced by source paper "tight conditional lower bounds for longest common increasing subsequence"):
  with members:
    - "on problems equivalent to min convolution"
    - "why is it hard to beat o n 2 for longest common weakly increasing subsequence"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "a simple linear space algorithm for computing a longest common increasing subsequence"
    - "which regular expression patterns are hard to match"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"

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.CC(Computational Complexity)