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 "truth serums for massively crowdsourced evaluation tasks"):
  Abstract: Incentivizing effort and eliciting truthful responses from agents in the absence of verifiability is a major challenge faced while crowdsourcing many types of evaluation tasks like labeling images, grading assignments in online courses, etc. In this paper, we propose new reward mechanisms for such settings that, unlike most previously studied mechanisms, impose minimal assumptions on the structure and knowledge of the underlying generating model, can account for heterogeneity in the agents' abilities, require no extraneous elicitation from them, and furthermore allow their beliefs to be (almost) arbitrary. Moreover, these mechanisms have the simple and intuitive structure of output agreement mechanisms, which, despite not incentivizing truthful behavior, have nevertheless been quite popular in practice. We achieve this by leveraging a typical characteristic of many of these settings, which is the existence of a large number of similar tasks.

Includes members:
  Member "peer prediction with heterogeneous tasks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "impact of social learning on privacy preserving data collection")
  Member "incentivizing evaluation via limited access to ground truth peer prediction makes things worse":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "credible sample elicitation")
  Member "a framework for designing information elicitation mechanisms that reward truth telling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "information gathering with peers submodular optimization with peer prediction constraints")
  Member "informed truthfulness in multi task peer prediction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surrogate scoring rules")
  Member "approval voting and incentives in crowdsourcing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uncertainty about uncertainty near optimal adaptive algorithms for estimating binary mixtures of unknown coins")
  Member "tuned models of peer assessment in moocs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "key phrase classification in complex assignments")
  Member "crowdsourced judgement elicitation with endogenous proficiency":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "surrogate scoring rules")

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.GT(Computer Science and Game Theory)