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: "on welfare approximation and stable pricing"
  Abstract: We study the power of item-pricing as a tool for approximately optimizing social welfare in a combinatorial market. We consider markets with $m$ indivisible items and $n$ buyers. The goal is to set prices to the items so that, when agents purchase their most demanded sets simultaneously, no conflicts arise and the obtained allocation has nearly optimal welfare. For gross substitutes valuations, it is well known that it is possible to achieve optimal welfare in this manner. We ask: can one achieve approximately efficient outcomes for valuations beyond gross substitutes? We show that even for submodular valuations, and even with only two buyers, one cannot guarantee an approximation better than $\Omega(\sqrt{m})$. The same lower bound holds for the class of single-minded buyers as well. Beyond the negative results on welfare approximation, our results have daunting implications on revenue approximation for these valuation classes: in order to obtain good approximation to the collected revenue, one would necessarily need to abandon the common approach of comparing the revenue to the optimal welfare; a fundamentally new approach would be required.

Connected through hyperedge HE-1 (induced by source paper "fair and truthful mechanisms for dichotomous valuations"):
  with members:
    - "maximum nash welfare and other stories about efx"
    - "envy freeness up to any item with high nash welfare the virtue of donating items"
    - "fair division of indivisible goods among strategic agents"
    - "competitive equilibrium with generic budgets beyond additive"
    - "a little charity guarantees almost envy freeness"
    - "the price of fairness for indivisible goods"
    - "fair division with bounded sharing"
    - "truthful allocation mechanisms without payments characterization and implications on fairness"

Connected through hyperedge HE-2 (induced by source paper "a general framework for endowment effects in combinatorial markets"):
  with members:
    - "combinatorial auctions with endowment effect"
    - "clearing markets via bundles"
    - "welfare and revenue guarantees for competitive bundling equilibrium"
    - "combinatorial walrasian equilibrium"
    - "combinatorial auctions with decreasing marginal utilities"

Connected through hyperedge HE-3 (induced by source paper "price doubling and item halving robust revenue guarantees for item pricing"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "envy free pricing in multi unit markets"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "pricing to maximize revenue and welfare simultaneously in large markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "secretary problems with non uniform arrival order"
    - "optimal auctions vs anonymous pricing"

Connected through hyperedge HE-4 (induced by source paper "posted pricing sans discrimination"):
  with members:
    - "do prices coordinate markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "the invisible hand of dynamic market pricing"
    - "sequential posted price mechanisms with correlated valuations"
    - "welfare maximization with production costs a primal dual approach"
    - "combinatorial auctions via posted prices"
    - "combinatorial walrasian equilibrium"
    - "welfare and profit maximization with production costs"

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.GT(Computer Science and Game Theory)