<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Molin Zhao: writing</title><description>Molin Zhao is a biomedical engineering student at UC Davis who decodes brain activity, takes models apart to see how they work, and builds things.</description><link>https://molinzhao.com/</link><item><title>Aligning a neural encoder to a language model, without phonemes</title><link>https://molinzhao.com/blog/contrastive-alignment/</link><guid isPermaLink="true">https://molinzhao.com/blog/contrastive-alignment/</guid><description>Contrastive alignment taught a speech encoder to pick the right sentence out of 704 a third of the time, with no phoneme labels. It did not make the encoder a better starting point for decoding.</description><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate></item><item><title>A diffusion language model as a brain-to-text decoder</title><link>https://molinzhao.com/blog/diffusion-decoder/</link><guid isPermaLink="true">https://molinzhao.com/blog/diffusion-decoder/</guid><description>Training the language model in a speech decoder by block diffusion, not left to right, cut word error rate by about ten points. The gain disappeared once the encoder had been trained on phonemes.</description><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate></item><item><title>Can a projector turn inner speech into attempted speech?</title><link>https://molinzhao.com/blog/inner-speech-projector/</link><guid isPermaLink="true">https://molinzhao.com/blog/inner-speech-projector/</guid><description>Inner speech looks like attempted speech, shifted and quieter. Reversing that with a linear map made the sentence easier to identify and did nothing for the synthesized voice.</description><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate></item><item><title>Place cells are easy to find. That&apos;s the problem.</title><link>https://molinzhao.com/blog/place-cells-are-easy-to-find/</link><guid isPermaLink="true">https://molinzhao.com/blog/place-cells-are-easy-to-find/</guid><description>Units that pass the rodent place-cell test turn up in raw pixels and in random networks. To find out whether a vision-language model knows where it is, I had to change its activations and watch the answer move.</description><pubDate>Mon, 09 Nov 2026 00:00:00 GMT</pubDate></item></channel></rss>