A staged knowledge-prompting method (KAAR) improves LLM test accuracy on ARC by about 5 absolute points over repeated-sampling plan-guided code generation, reaching 35% with GPT-o3-mini.
Program synthesis.Foundations and Trends® in Programming Languages, 4:1–119, 2017
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark
A staged knowledge-prompting method (KAAR) improves LLM test accuracy on ARC by about 5 absolute points over repeated-sampling plan-guided code generation, reaching 35% with GPT-o3-mini.