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Zonghui Liu

Publications and source records attributed to Zonghui Liu.

2 recordsLinked to original sources

Tilting theory on continuous quivers (I) maximal rigid and tilting subcategories

Let $\mathrm{rep}(\mathbb I)$ be the category of finitely generated persistence modules on the interval $\mathbb I\subseteq\mathbb R$. We study the maximal rigid subcategories of $\mathrm{rep}(\mathbb I)$. Maximal rigid interval consistent subcategories are classified via tilting modules over the corresponding discrete type $A$ quiver. We compare several related notions, (weak) tilting and maximal rigidity, in both the context of hereditary abelian categories with enough projective objects and $\mathrm{rep}(\mathbb I)$ and prove that every maximal rigid interval consistent subcategory is weak tilting and every maximal rigid consistent below subcategory is tilting. We also establish a continuous analogue of Ingalls-Thomas's bijection by showing a bijection between integrally supported maximal rigid consistent below subcategories and integrally generated torsion classes.

math.RT↗

Natural Language Processing with Commonsense Knowledge: A Survey

Commonsense knowledge is essential for advancing natural language processing (NLP) by enabling models to engage in human-like reasoning, which requires a deeper understanding of context and often involves making inferences based on implicit external knowledge. This paper explores the integration of commonsense knowledge into various NLP tasks. We begin by reviewing prominent commonsense knowledge bases and then discuss the benchmarks used to evaluate the commonsense reasoning capabilities of NLP models, particularly language models. Furthermore, we highlight key methodologies for incorporating commonsense knowledge and their applications across different NLP tasks. The paper also examines the challenges and emerging trends in enhancing NLP systems with commonsense reasoning. All literature referenced in this survey can be accessed via our GitHub repository: https://github.com/yuboxie/awesome-commonsense.

cs.CL↗