Understanding intermediate layers using linear classifier probes · HackerPapers discussions

Understanding intermediate layers using linear classifier probes — mentioned by sdenton4

Mon, 15 Sep 2025 16:50:47 GMT

IME: most of the reviewers in the big ML conferences are second-year phd students sent into the breach against the overwhelming tide of 10k submissions... Their review comments are often somewhere between useless and actively promoting scientific dishonesty. Sometimes we get good reviewers, who ask questions and make comments which improve the quality of a paper, but I don't really expect it in the conference track. It's much more common to get good reviewers in smaller journals, in domains where the reviewers are experts and care about the subject matter. OTOH, the turnaround for publication…

Paper and discussion history. A mention is not an endorsement.

Understanding intermediate layers using linear classifier probes — mentioned by JoshuaDavid

Wed, 14 Jun 2023 01:48:01 GMT

Slightly off-topic, but I am just starting to learn about the field, and saw > GPT4 still projects information into some highly non-linear latent space and samples from that Do you have more information/know where I can find things to read about the "highly non-linear" part of that? I've been reading some stuff[1][2][3] about smaller models, and my impression has been that the latent space is shockingly linear for those ones. But counterexamples would be informative, especially if it's something that only happens with larger models. ----- [1] https://arxiv.org/abs/2209.15162 [2]…

Paper and discussion history. A mention is not an endorsement.