Understanding Reasoning in Thinking Language Models via Steering Vectors — mentioned by x313

Tue, 03 Nov 2026 16:09:16 GMT

I work in this field (mech interp research) and I agree, the original post is definitely misleading. Some overselling in research is normal but it's a bit much. First, the key result has nothing to do with making Qwen better at math, it just reduces reasoning loops. Reasoning loops are a simple problem: the model generates the </think> token (which closes reasoning) with too low probability. You can fix this with simple steering approaches where you add a vector to different components of the LLM (https://arxiv.org/abs/2503.22048, https://arxiv.org/abs/2506.18167, etc). The method Astra used…

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Understanding Reasoning in Thinking Language Models via Steering Vectors · HackerPapers discussions

Understanding Reasoning in Thinking Language Models via Steering Vectors — mentioned by x313