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cs.CL2024
: Towards Measuring Class-wise Hardness through Modelling Class Semantics
Fengyu Cai, Xinran Zhao, Hongming Zhang +2
Recent advances in measuring hardness-wise properties of data guide language models in sample selection within low-resource scenarios. However, class-specific properties are overlo…
cs.CL2024★ 1 cited
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models
Xinran Zhao, Hongming Zhang, Xiaoman Pan +4
For a LLM to be trustworthy, its confidence level should be well-calibrated with its actual performance. While it is now common sense that LLM performances are greatly impacted by…