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Replacing just 12% of traditional training data with OctoLong's curated code contexts leads to substantial improvements in long-range retrieval and state tracking for language models.
Current code reward models are myopic, mostly rewarding functional correctness, but Themis-RM learns to score code across multiple criteria and languages, opening the door to more nuanced and useful code generation.