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 "exploring structural inductive biases in emergent communication"):
  Abstract: Human language and thought are characterized by the ability to systematically generate a potentially infinite number of complex structures (e.g., sentences) from a finite set of familiar components (e.g., words). Recent works in emergent communication have discussed the propensity of artificial agents to develop a systematically compositional language through playing co-operative referential games. The degree of structure in the input data was found to affect the compositionality of the emerged communication protocols. Thus, we explore various structural priors in multi-agent communication and propose a novel graph referential game. We compare the effect of structural inductive bias (bag-of-words, sequences and graphs) on the emergence of compositional understanding of the input concepts measured by topographic similarity and generalization to unseen combinations of familiar properties. We empirically show that graph neural networks induce a better compositional language prior and a stronger generalization to out-of-domain data. We further perform ablation studies that show the robustness of the emerged protocol in graph referential games.

Includes members:
  Member "on the interaction between supervision and self play in emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity bandwidth and compositionality in emergent language learning")
  Member "measuring compositionality in representation learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linguistic generalization and compositionality in modern artificial neural networks")
  Member "ease of teaching and language structure from emergent communication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "clutrr a diagnostic benchmark for inductive reasoning from text":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "evaluating logical generalization in graph neural networks")
  Member "egg a toolkit for research on emergence of language in games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards graph representation learning in emergent communication")
  Member "how agents see things on visual representations in an emergent language game":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards graph representation learning in emergent communication")
  Member "emergence of linguistic communication from referential games with symbolic and pixel input":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "natural language does not emerge naturally in multi agent dialog":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the interaction between supervision and self play in emergent communication")

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)