14 citations · 18 across the 4 of their papers we have counts for
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cs.CL2024
Concise and Precise Context Compression for Tool-Using Language Models
Yang Xu, Yunlong Feng, Honglin Mu +9
Through reading the documentation in the context, tool-using language models can dynamically extend their capability using external tools. The cost is that we have to input lengthy…
cs.CL2022★ 14 cited
MetaPrompting: Learning to Learn Better Prompts
Yutai Hou, Hongyuan Dong, Xinghao Wang +2
Prompting method is regarded as one of the crucial progress for few-shot nature language processing. Recent research on prompting moves from discrete tokens based ``hard prompts''…
cs.CL2021★ 4 cited
A Self-supervised Method for Entity Alignment
Xiao Liu, Haoyun Hong, Xinghao Wang +4
Entity alignment, aiming to identify equivalent entities across different knowledge graphs (KGs), is a fundamental problem for constructing large-scale KGs. Over the course of its…