3 citations · 8 across the 19 of their papers we have counts for
4 papers · 1 filter
Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graph
Jingwei Wang, Zai Zhang, Hao Qian +7
Teaching large language models (LLMs) to use tools is crucial for improving their problem-solving abilities and expanding their applications. However, effectively using tools is ch…
POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications
Chunjing Gan, Dan Yang, Binbin Hu +5
Large language models (LLMs) have become a disruptive force in the industry, introducing unprecedented capabilities in natural language processing, logical reasoning and so on. How…
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
Chunjing Gan, Dan Yang, Binbin Hu +9
In recent years, large language models (LLMs) have made remarkable achievements in various domains. However, the untimeliness and cost of knowledge updates coupled with hallucinati…
Your decision path does matter in pre-training industrial recommenders with multi-source behaviors
Chunjing Gan, Binbin Hu, Bo Huang +5
Online service platforms offering a wide range of services through miniapps have become crucial for users who visit these platforms with clear intentions to find services they are…