533 citations · 1.1k across the 53 of their papers we have counts for
4 papers · 1 filter
ArchitectureIQ: On the Measure of Training Intuition
Zirui Ren, Shaoyang Guo, Chencheng Tang +9
Top researchers have good intuition, but do language models have as good intuition about model training as top AI researchers? To measure model intuition of LLMs and humans, we int…
Clearing the Fog: Towards Installing and Refining Proactive Exploration Capabilities in LLM Agents
Zhizhao Guan, Chen Huang, Ziming Liu +5
We study proactive exploration in LLM agents, i.e., the ability to explore an environment to acquire information that improves future decision-making. In this regard, we first iden…
Do Two AI Scientists Agree?
Xinghong Fu, Ziming Liu, Max Tegmark
When two AI models are trained on the same scientific task, do they learn the same theory or two different theories? Throughout history of science, we have witnessed the rise and f…
How Diffusion Models Learn to Factorize and Compose
Qiyao Liang, Ziming Liu, Mitchell Ostrow +1
Diffusion models are capable of generating photo-realistic images that combine elements which likely do not appear together in the training set, demonstrating the ability to \texti…