2 citations · 6 across the 4 of their papers we have counts for
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cs.CL2025
Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using the Consensual Assessment Technique
Piotr Sawicki, Marek Grześ, Dan Brown +1
This study adapts the Consensual Assessment Technique (CAT) for Large Language Models (LLMs), introducing a novel methodology for poetry evaluation. Using a 90-poem dataset with a…
cs.CL2023★ 2 cited
Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording
Aisha Khatun, Daniel G. Brown
Large language models (LLMs) have become mainstream technology with their versatile use cases and impressive performance. Despite the countless out-of-the-box applications, LLMs ar…
cs.CL2023★ 2 cited
Bits of Grass: Does GPT already know how to write like Whitman?
Piotr Sawicki, Marek Grzes, Fabricio Goes +3
This study examines the ability of GPT-3.5, GPT-3.5-turbo (ChatGPT) and GPT-4 models to generate poems in the style of specific authors using zero-shot and many-shot prompts (which…