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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A framework decomposes RL advantage functions into gradient mass axes, showing trade-offs shift during training and motivating FADE, which adapts weights dynamically to accelerate convergence and improve accuracy-diversity trade-offs.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Nested unit-test coverage in code RL reveals a correctness, efficiency frontier that extrapolative weight averaging extends, enabling complementary checkpoints that improve pass@250 by 3.3%.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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