[D] Data curation and targeted replacement as a pre-training alignment and contr

<!-- SC_OFF --><div class="md"><p>Hi All, I've been running experiments on targeted SFT for specific capability dimensions on a 31B model. After running small training run to

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<!-- SC_OFF --><div class="md"><p>Every time one of our agents made a bad call in production, we had the same problem. Logs showed what happened. Nothing showed why it decided to

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<!-- SC_OFF --><div class="md"><p>Disclosure: I built LabelSets (labelsets.ai). Sharing the technical approach behind how we score dataset quality.</p> <p>THE PROBLEM</p> <p>Most

<!-- SC_OFF --><div class="md"><p>Link to the paper:</p> <p><a

<!-- SC_OFF --><div class="md"><p>&#x200b;</p> <p>## Abstract</p> <p>Post-training makes language models more decisive without necessarily making them more accurate — and we find