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 a theorem of lovasz that hom cdot h determines the isomorhphism type of h"):
  Abstract: Graph homomorphism has been an important research topic since its introduction [13]. Stated in the language of binary relational structures in this paper [13], Lovasz proved a fundamental theorem that the graph homomorphism function $G \mapsto \hom(G, H)$ for 0-1 valued $H$ (as the adjacency matrix of a graph) determines the isomorphism type of $H$. In the past 50 years various extensions have been proved by Lovasz and others [14, 9, 1, 18, 16]. These extend the basic 0-1 case to admit vertex and edge weights; but always with some restrictions such as all vertex weights must be positive. In this paper we prove a general form of this theorem where $H$ can have arbitrary vertex and edge weights. An innovative aspect is we prove this by a surprisingly simple and unified argument. This bypasses various technical obstacles and unifies and extends all previous known versions of this theorem on graphs. The constructive proof of our theorem can be used to make various complexity dichotomy theorems for graph homomorphism effective, i.e., an algorithm such that for any $H$ either outputs a P-time algorithm solving $\hom(\cdot, H)$ or a P-time reduction from a canonical #P-hard problem to $\hom(\cdot, H)$.

Includes members:
  Member "perfect matchings rank of connection tensors and graph homomorphisms":
    also connected through other hyperedges:
      (none)
  Member "counting homomorphisms and partition functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a dichotomy for bounded degree graph homomorphisms with nonnegative weights")
  Member "a decidable dichotomy theorem on directed graph homomorphisms with non negative weights":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a dichotomy for bounded degree graph homomorphisms with nonnegative weights")
  Member "graph homomorphisms with complex values a dichotomy theorem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a dichotomy for bounded degree graph homomorphisms with nonnegative weights")
  Member "a complexity dichotomy for partition functions with mixed signs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a dichotomy for bounded degree graph homomorphisms with nonnegative weights")

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.DM(Discrete Mathematics)