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Minor architectural tweaks can lead to a staggering 47% drop in long context performance, challenging assumptions about model design.
Decomposer achieves superior MIDI reconstruction fidelity and code readability compared to existing models, transforming how we approach symbolic music decompilation.
On-policy reward modeling with LLM judges not only unlocks significant performance gains on complex mathematical reasoning tasks, but also generalizes to improve performance on simpler numerical and multiple-choice benchmarks.
