The authors of "Do LLMs Build World Representations? Probing Through the Lens ..." propose a framework for probing world representations in Large Language Models using state abstraction theory from reinforcement learning, which distinguishes between general abstractions that facilitate predicting future states and goal-oriented abstractions that guide actions to accomplish tasks.

Authors

• Person: Not available Organization: OpenReview
  Do LLMs Build World Representations? Probing Through the Lens of...
• Person: Not available Organization: NeurIPS
  Do LLMs Build World Representations? Probing Through ...
• Person: Not available Organization: Semantic Scholar
  Do LLMs Build World Representations? Probing Through the Lens ...

Sources

• Do LLMs Build World Representations? Probing Through the Lens of... openreview.net OpenReview via serper
• Do LLMs Build World Representations? Probing Through ... neurips.cc NeurIPS via serper
• Do LLMs Build World Representations? Probing Through the Lens ... proceedings.neurips.cc NeurIPS via serper
• Do LLMs Build World Representations? Probing Through the Lens ... www.semanticscholar.org Semantic Scholar via serper

Referenced by nodes (2)

• Large Language Models concept
• reinforcement learning concept