Improving LLMs: Steering Towards Truth and Self-Evaluation
KordingLab · x · 2026-08-26
This post proposes two strategies for enhancing LLM output quality. First, in domains where 'truth' is definable (like math or coding), actively push the model towards that truth during training. Second, in open domains without clear truth definitions, use LLMs to perform 'self-evaluation' to check their own answers. These methods aim to move beyond simple probabilistic generation.
Related event: The Recipe Behind Modern Thinking Machines and How to Improve LLMs(2 posts)→
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