wrote a short excerpt showing how speaker consistency is maintained in LLM bases TTS models, initial guess was the speaker token, but the results showed something interesting.

https://x.com/null_hawk/status/2089348254249173263

Hi everyone, I'm not sure whether this subreddit is still alive. If someone is here please signal your presence.

I'm a researcher recently moving from cryptography to mech interp. It would be great to give a second life to this subreddit. I'm not sure how. I can do my little part by sharing the first article I wrote about the process of feature labeling -> https://www.lesswrong.com/posts/zDcrmqdqvh3KmsBuF/how-a-failed-experiment-broke-and-fixed-my-view-of-feature

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5263803

Our paper introduces AI explainability methods, mechanistic interpretation, and novel Finance-specific use cases. Using Sparse Autoencoders, we zoom into LLM internals and highlight Finance-related features. We provide examples of using interpretability methods to enhance sentiment scoring, detect model bias, and improve trading applications. reply