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 the interaction between supervision and self play in emergent communication"):
  Abstract: A promising approach for teaching artificial agents to use natural language involves using human-in-the-loop training. However, recent work suggests that current machine learning methods are too data inefficient to be trained in this way from scratch. In this paper, we investigate the relationship between two categories of learning signals with the ultimate goal of improving sample efficiency: imitating human language data via supervised learning, and maximizing reward in a simulated multi-agent environment via self-play (as done in emergent communication), and introduce the term supervised self-play (S2P) for algorithms using both of these signals. We find that first training agents via supervised learning on human data followed by self-play outperforms the converse, suggesting that it is not beneficial to emerge languages from scratch. We then empirically investigate various S2P schedules that begin with supervised learning in two environments: a Lewis signaling game with symbolic inputs, and an image-based referential game with natural language descriptions. Lastly, we introduce population based approaches to S2P, which further improves the performance over single-agent methods.

Includes members:
  Member "anti efficient encoding in emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity bandwidth and compositionality in emergent language learning")
  Member "emergent linguistic phenomena in multi agent communication games":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "entropy minimization in emergent languages")
  Member "capacity bandwidth and compositionality in emergent language learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards graph representation learning in emergent communication")
  Member "ease of teaching and language structure from emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploring structural inductive biases in emergent communication")
  Member "on the pitfalls of measuring emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "emergent communication with world models")
  Member "mastering emergent language learning to guide in simulated navigation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to request guidance in emergent communication")
  Member "countering language drift via visual grounding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "i love your chain mail making knights smile in a fantasy game world open domain goal orientated dialogue agents")
  Member "emergence of compositional language with deep generational transmission":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on emergent communication in competitive multi agent teams")

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.CL(Computation and Language)