6 papers · 1 filter
What Gets Unmasked First? Trajectory Analysis of Diffusion Models for Graph-to-Text Generation
Qing Wang, Jacob Devasier, Chengkai Li
We present the first systematic study of masked diffusion language models (MDLMs) for graph-to-text generation. We analyze MDLM generation trajectories -- the order in which tokens…
Towards a More Generalized Approach in Open Relation Extraction
Qing Wang, Yuepei Li, Qiao Qiao +2
Open Relation Extraction (OpenRE) seeks to identify and extract novel relational facts between named entities from unlabeled data without pre-defined relation schemas. Traditional…
Bridge: A Unified Framework to Knowledge Graph Completion via Language Models and Knowledge Representation
Qiao Qiao, Yuepei Li, Qing Wang +2
Knowledge graph completion (KGC) is a task of inferring missing triples based on existing Knowledge Graphs (KGs). Both structural and semantic information are vital for successful…
Investigating Context-Faithfulness in Large Language Models: The Roles of Memory Strength and Evidence Style
Yuepei Li, Kang Zhou, Qiao Qiao +3
Retrieval-augmented generation (RAG) improves Large Language Models (LLMs) by incorporating external information into the response generation process. However, how context-faithful…
Re-Examine Distantly Supervised NER: A New Benchmark and a Simple Approach
Yuepei Li, Kang Zhou, Qiao Qiao +2
Distantly-Supervised Named Entity Recognition (DS-NER) uses knowledge bases or dictionaries for annotations, reducing manual efforts but rely on large human labeled validation set.…
Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence Pairs
Qing Wang, Kang Zhou, Qiao Qiao +2
Unsupervised relation extraction (URE) aims to extract relations between named entities from raw text without requiring manual annotations or pre-existing knowledge bases. In recen…