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Zhanhao Xiao

4 accepted papers

2023

Exploring the Capacity of Pretrained Language Models for Reasoning about Actions and Change

ACL 2023long

Reasoning about actions and change (RAC) is essential to understand and interact with the ever-changing environment. Previous AI research has shown the importance of fundamental and indispensable knowledge of actions, i.e., preconditions and effects. However, traditional methods rely on logical form…

2023

Gradient-Based Mixed Planning with Symbolic and Numeric Action Parameters (Extended Abstract)

IJCAI 2023poster

Dealing with planning problems with both logical relations and numeric changes in real-world dynamic environments is challenging. Existing numeric planning systems for the problem often discretize numeric variables or impose convex constraints on numeric variables, which harms the performance when s…

Cited by 0SourcePDFScholar
2022

Knowledge Compilation Meets Logical Separability

AAAI 2022technical

Knowledge compilation is an alternative solution to address demanding reasoning tasks with high complexity via converting knowledge bases into a suitable target language. Interestingly, the notion of logical separability, proposed by Levesque, offers a general explanation for the tractability of cla…

Cited by 1SourcePDFScholar
2022

LogicNMR: Probing the Non-monotonic Reasoning Ability of Pre-trained Language Models

EMNLP 2022finding

The logical reasoning capabilities of pre-trained language models have recently received much attention. As one of the vital reasoning paradigms, non-monotonic reasoning refers to the fact that conclusions may be invalidated with new information. Existing work has constructed a non-monotonic inferen…