6 citations · 6 across the 9 of their papers we have counts for
4 papers · 1 filter
On Calibration of Large Language Models: From Response To Capability
Sin-Han Yang, Cheng-Kuang Wu, Chieh-Yen Lin +3
Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on response-level confidence, which estim…
BILLY: Steering Large Language Models via Merging Persona Vectors for Creative Generation
Tsung-Min Pai, Jui-I Wang, Li-Chun Lu +3
Multi-LLM systems enhance the creativity of large language models by simulating human collective intelligence but suffer from significant drawbacks, such as high computational cost…
Rethinking Creativity Evaluation: A Critical Analysis of Existing Creativity Evaluations
Li-Chun Lu, Miri Liu, Pin-Chun Lu +3
We examine, analyze, and compare four representative creativity measures--perplexity, LLM-as-a-Judge, the Creativity Index (CI; measuring n-gram overlap with web corpora), and synt…
LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play
Li-Chun Lu, Shou-Jen Chen, Tsung-Min Pai +3
Large language models (LLMs) have shown exceptional proficiency in natural language processing but often fall short of generating creative and original responses to open-ended ques…