Microsoft’s new Pareto Optimal Self-Supervision Framework Automatically Corrects Language Models to Boost GPT SOTA Records | Synced

In a new paper Automatic Calibration and Error Correction for Large Language Models via Pareto Optimal Self-Supervision, a Microsoft team research team presents Pareto optimal self-supervision, a flexible framework that leverages programmatic supervision to automatically calibrate and correct error for Large language models without extra manual efforts.