21 citations · 86 across the 12 of their papers we have counts for
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3 papers · 1 filter
cs.IR2023★ 19 cited
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting
Zhen Qin, Rolf Jagerman, Kai Hui +9
Ranking documents using Large Language Models (LLMs) by directly feeding the query and candidate documents into the prompt is an interesting and practical problem. However, researc…
cs.CL2023★ 11 cited
SLiC-HF: Sequence Likelihood Calibration with Human Feedback
Yao Zhao, Rishabh Joshi, Tianqi Liu +3
Learning from human feedback has been shown to be effective at aligning language models with human preferences. Past work has often relied on Reinforcement Learning from Human Feed…
cs.LG2023★ 5 cited
Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation
Rongzhi Zhang, Jiaming Shen, Tianqi Liu +4
Knowledge distillation is a popular technique to transfer knowledge from large teacher models to a small student model. Typically, the student learns to imitate the teacher by mini…