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Long-form video generation struggles with transitions, scoring only 0.256 on transition quality even when prompt fulfillment is high (0.71), revealing a critical bottleneck exposed by the new DirectorBench diagnostic benchmark.
Saturated LLM benchmarks can be revived without creating new datasets: a self-improving LLM judge in an elimination tournament recovers ranking signal and breaks ties.
Stop ignoring the future: adaptively weighting future user interactions during training can significantly boost sequential recommendation accuracy.
