Prompt optimization per model substantially alters LLM rankings on both public and internal benchmarks compared to using fixed unoptimized prompts.
The final score reported for this task is the average precision of the JSON entries generated by the model
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Optimization before Evaluation: Evaluation with Unoptimised Prompts Can be Misleading
Prompt optimization per model substantially alters LLM rankings on both public and internal benchmarks compared to using fixed unoptimized prompts.