Contrastive targeted SFT as a mechinterp method - has anyone mapped causal depen

<!-- SC_OFF --><div class="md"><p>Hi, <a href="/r/MachineLearning">r/MachineLearning</a>: has much research been done in large-scale training scenarios where undesirable data has

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1sufmrp/the_eu_and_the_white_house_published_documents/"> <img alt="The EU and the White House

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sez79x/towards_a_bitter_lesson_of_optimization_when/"> <img alt="Towards a Bitter Lesson of Optimization:

<!-- SC_OFF --><div class="md"><p><strong>Noam Brown</strong> — OpenAI Research Scientist and co-creator of o1, Libratus, and Cicero — sat down with Dwarkesh Patel for a 1h 20m

<!-- 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

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

<!-- SC_OFF --><div class="md"><p>I've been using AI extensively for ML research, and I've noticed a bottleneck: brainstorming research directions and generating smoke run

<!-- 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