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most citedDialogue Is Not Enough to Make a Communicative BabyLM (But Neither Is Developmentally Inspired Reinforcement Learning)

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cs.CL2024

BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency

Akari Haga, Akiyo Fukatsu, Miyu Oba +2

While current large language models have achieved a remarkable success, their data efficiency remains a challenge to overcome. Recently it has been suggested that child-directed sp…

cs.CL2024

NeLLCom-X: A Comprehensive Neural-Agent Framework to Simulate Language Learning and Group Communication

Yuchen Lian, Tessa Verhoef, Arianna Bisazza

Recent advances in computational linguistics include simulating the emergence of human-like languages with interacting neural network agents, starting from sets of random symbols.…