3 citations · 8 across the 19 of their papers we have counts for
4 papers · 2 filters
Have We Designed Generalizable Structural Knowledge Promptings? Systematic Evaluation and Rethinking
Yichi Zhang, Zhuo Chen, Lingbing Guo +8
Large language models (LLMs) have demonstrated exceptional performance in text generation within current NLP research. However, the lack of factual accuracy is still a dark cloud h…
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs
Junjie Wang, Mingyang Chen, Binbin Hu +10
Improving the performance of large language models (LLMs) in complex question-answering (QA) scenarios has always been a research focal point. Recent studies have attempted to enha…
Multi-domain Knowledge Graph Collaborative Pre-training and Prompt Tuning for Diverse Downstream Tasks
Yichi Zhang, Binbin Hu, Zhuo Chen +6
Knowledge graphs (KGs) provide reliable external knowledge for a wide variety of AI tasks in the form of structured triples. Knowledge graph pre-training (KGP) aims to pre-train ne…
Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs
Junjie Wang, Dan Yang, Binbin Hu +3
In this paper, we explore a new way for user targeting, where non-expert marketers could select their target users solely given demands in natural language form. The key to this is…