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Ziquan Fu

3 accepted papers

2023

Distilling Script Knowledge from Large Language Models for Constrained Language Planning

ACL 2023long

In everyday life, humans often plan their actions by following step-by-step instructions in the form of goal-oriented scripts. Previous work has exploited language models (LMs) to plan for abstract goals of stereotypical activities (e.g., “make a cake”), but leaves more specific goals with multi-fac…

2023

Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledge

ACL 2023long

Large language models (LLMs) have been widely studied for their ability to store and utilize positive knowledge. However, negative knowledge, such as “lions don’t live in the ocean”, is also ubiquitous in the world but rarely mentioned explicitly in text. What do LLMs know about negative knowledge?T…

2022

E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning

ACL 2022findings

The ability to recognize analogies is fundamental to human cognition. Existing benchmarks to test word analogy do not reveal the underneath process of analogical reasoning of neural models. Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-…

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