7 papers
Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variables
Weizhi Fei, Hang Yin, Zihao Wang +3
Complex Query Answering (CQA) is a fundamental knowledge representation and reasoning task over incomplete knowledge graphs (KGs). Answering existential first-order queries with $k…
is Theoretically Large Enough for Embedding-based Top- Retrieval
Zihao Wang, Hang Yin, Lihui Liu +4
This paper studies the Minimal Embeddable Dimension (MED): the least dimension in which there exists a configuration of object vectors so that every subset of size at most …
Efficient and Scalable Neural Symbolic Search for Knowledge Graph Complex Query Answering
Weizhi Fei, Zihao Wang, hang Yin +3
Complex Query Answering (CQA) is a crucial reasoning task over Knowledge Graphs (KGs), which aims to answer first-order logical queries from incomplete KGs. While existing neural-s…
LegalCiteBench: Evaluating Citation Reliability in Legal Language Models
Sijia Chen, Hang Yin, Shunfan Zhou
Large language models (LLMs) are increasingly integrated into legal drafting and research workflows, where incorrect citations or fabricated precedents can cause serious profession…
Enhancing Transformers for Generalizable First-Order Logical Entailment
Tianshi Zheng, Jiazheng Wang, Zihao Wang +5
Transformers, as the fundamental deep learning architecture, have demonstrated great capability in reasoning. This paper studies the generalizable first-order logical reasoning abi…
Extending Complex Logical Queries on Uncertain Knowledge Graphs
Weizhi Fei, Zihao Wang, Hang Yin +2
The study of machine learning-based logical query answering enables reasoning with large-scale and incomplete knowledge graphs. This paper advances this area of research by address…