4 papers
Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments
Ziyan Luo, Tianwei Ni, Pierre-Luc Bacon +2
A key approach to state abstraction is approximating behavioral metrics (notably, bisimulation metrics) in the observation space and embedding these learned distances in the repres…
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation
Bowen Li, Zhaoyu Li, Qiwei Du +10
Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems, which integrate symbolic reasoning into deep neural networks. However, most of the existing b…
Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning
Zenan Li, Zhaoyu Li, Wen Tang +6
Large language models (LLMs) can prove mathematical theorems formally by generating proof steps (\textit{a.k.a.} tactics) within a proof system. However, the space of possible tact…
Decoupling Training-Free Guided Diffusion by ADMM
Youyuan Zhang, Zehua Liu, Zenan Li +3
In this paper, we consider the conditional generation problem by guiding off-the-shelf unconditional diffusion models with differentiable loss functions in a plug-and-play fashion.…