43 citations · 151 across the 29 of their papers we have counts for
4 papers · 1 filter
End-to-End Ontology Learning with Large Language Models
Andy Lo, Albert Q. Jiang, Wenda Li +1
Ontologies are useful for automatic machine processing of domain knowledge as they represent it in a structured format. Yet, constructing ontologies requires substantial manual eff…
Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe
Alicja Ziarko, Albert Q. Jiang, Bartosz Piotrowski +3
Text embeddings are essential for many tasks, such as document retrieval, clustering, and semantic similarity assessment. In this paper, we study how to contrastively train text em…
Autoformalization with Large Language Models
Yuhuai Wu, Albert Q. Jiang, Wenda Li +4
Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could adv…
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
Yuhuai Wu, Markus Rabe, Wenda Li +3
While designing inductive bias in neural architectures has been widely studied, we hypothesize that transformer networks are flexible enough to learn inductive bias from suitable g…