Large Language Models Do Not Always Need Readable Language

Beyond Autoregression: LLaDA2.1 and the Case for Self-Editing Language Models

Exploring the Limitations of Language Models as World Models

The article argues that language models (LLMs) are not world models, despite their complexity and capabilities. The author provides examples

ACM Transactions on Asian and Low-Resource Language Information Processing (tallip) Vol 25, Issue 6

Large Language Models Often Know When They Are Being Evaluated

ACM Transactions on Asian and Low-Resource Language Information Processing (tallip) Vol 25, Issue 7

Scaling Laws Limit Reliability of Large Language Models, Study Finds

This research paper demonstrates that the scaling laws governing large language models (LLMs) fundamentally limit their ability to improve p