5 papers · 1 filter
Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models
Xukai Liu, Ye Liu, Jipeng Zhang +3
Large language models (LLMs) perform well on multi-hop reasoning, yet how they internally compose multiple facts remains unclear. Recent work proposes \emph{hop-aligned circuit hyp…
Self-Reflective Planning with Knowledge Graphs: Enhancing LLM Reasoning Reliability for Question Answering
Jiajun Zhu, Ye Liu, Meikai Bao +3
Recently, large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, yet they remain prone to hallucinations when reasoning with i…
Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities
Changchun Liu, Kai Zhang, Junzhe Jiang +3
Chinese Spelling Correction (CSC) is a critical task in natural language processing, aimed at detecting and correcting spelling errors in Chinese text. This survey provides a compr…
OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting
Xukai Liu, Ye Liu, Kai Zhang +3
Entity Linking (EL) is the process of associating ambiguous textual mentions to specific entities in a knowledge base. Traditional EL methods heavily rely on large datasets to enha…
Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language Models
Ye Liu, Kai Zhang, Aoran Gan +4
Few-Shot Relation Extraction (FSRE), a subtask of Relation Extraction (RE) that utilizes limited training instances, appeals to more researchers in Natural Language Processing (NLP…