29 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals
Lida Chen, Zujie Liang, Xintao Wang +7
Large language models (LLMs) have achieved great success, but their occasional content fabrication, or hallucination, limits their practical application. Hallucination arises becau…
cs.CL2023★ 29 cited
How well do Large Language Models perform in Arithmetic tasks?
Zheng Yuan, Hongyi Yuan, Chuanqi Tan +2
Large language models have emerged abilities including chain-of-thought to answer math word problems step by step. Solving math word problems not only requires abilities to disasse…
cs.CL2022
STT: Soft Template Tuning for Few-Shot Adaptation
Ping Yu, Wei Wang, Chunyuan Li +3
Prompt tuning has been an extremely effective tool to adapt a pre-trained model to downstream tasks. However, standard prompt-based methods mainly consider the case of sufficient d…