dailyai.report

The LACE framework replaces isolated reasoning paths with a coordinated process using cross-thread attention. Researchers used a synthetic data pipeline to teach models how to share insights and correct errors during inference. This approach reduces redundant failures common in parallel sampling. Practitioners can now implement collaborative error-correction without relying on natural training data.