How I Study AI - Learn AI Papers & Lectures the Easy Way

Language of Thought Shapes Output Diversity in Large Language Models

Intermediate

Shaoyang Xu, Wenxuan ZhangJan 16arXiv

The paper shows that changing the language a model 'thinks in' (its language of thought) can make its English answers more varied without making them much worse in quality.

#language of thought#output diversity#multilingual reasoning

Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

Beginner

Yihong Liu, Raoyuan Zhao et al.Jan 6arXiv

Large reasoning models can often find the right math answer in their “head” before finishing their written steps, but this works best in languages with lots of training data like English and Chinese.

#latent reasoning#chain-of-thought#multilingual LLMs

Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits

Intermediate

Amirhosein Ghasemabadi, Di NiuDec 23arXiv

Large language models often sound confident even when they are wrong, and existing ways to catch mistakes are slow or not very accurate.

#self-awareness#large language models#hidden states

Papers3

Language of Thought Shapes Output Diversity in Large Language Models

Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits