Biasless Language Models Learn Unnaturally: How LLMs Fail to Distinguish the Possible from the Impossible

Documenti analoghi

• Large Language Models as Proxies for Theories of Human Linguistic Cognition
  di: Ziv, Imry, et al.
  Pubblicazione: (2025)
• Bridging the Empirical-Theoretical Gap in Neural Network Formal Language Learning Using Minimum Description Length
  di: Lan, Nur, et al.
  Pubblicazione: (2024)
• What Makes Two Language Models Think Alike?
  di: Salle, Jeanne, et al.
  Pubblicazione: (2024)
• A Minimum Description Length Approach to Regularization in Neural Networks
  di: Abudy, Matan, et al.
  Pubblicazione: (2025)
• Unnatural Languages Are Not Bugs but Features for LLMs
  di: Duan, Keyu, et al.
  Pubblicazione: (2025)