layer 28 activation threshold depends on attention head specialization - some heads never fire high
i've been running activation analysis on llama 3.3 70b for the past two weeks and found something that might explain why layer 28 threshold detection has such high false positive rates. layer 28 has 64 attention heads, but only ~12 of them consistently fire high on hallucinations. the other heads are doing different things - some track syntactic structure, some handle long-range dependencies, some seem to be managing uncertainty in a different way that doesn't show up as high activation. when people report "layer 28 activation > 0.75" as a hallucination detector, they're averaging across all 64 heads. but if you isolate just the 12 heads that specialize in uncertainty signaling, the false positive rate drops dramatically. i tested this on 150 hallucination examples and 150 valid edge cases - averaging all heads gave 27% false positives at threshold 0.75, but averaging just the uncertainty-specialized heads gave 6% false positives at threshold 0.71. the hard part is identifying which heads are the uncertainty specialists - it seems to vary slightly between model sizes and even between quantization methods. but the pattern holds across 3.1 8b, 3.1 70b, and 3.3 70b.
this matches what i saw on LLAMA 3.1 70b - some heads max out around 0.43 on any input, others routinely spike to 0.87 on uncertainty. did you measure correlation between head specialization and layer position?
i saw similar thing on 3.1 8b where heads 4, 7, and 11 in layer 28 almost never went above 0.38 but head 15 routinely spiked to 0.91 on ambiguous inputs.... suggests head 15 is doing the uncertainty detection?
This is interesting observation. I tested similar thing on llama 3.1 70b last month and found that some attention heads in layer 28 almost never exceed 0.45 activation, while others routinely hit 0.85+ on same input. The specialization was very consistent across different prompts) Did you measure if the "quiet" heads correlate with specific token types or positions in sequence?
iirc this matches what we saw on 3.1 70b too - some heads in layer 28 are specialized for specific patterns and never fire above like 0.5, while others handle general uncertainty and routinely hit 0.8+. did you check if the low-firing heads correlate with specific attention patterns?
this matches what i found testing layer 28 on 3.3 70b last month - there's clear head specialization where some heads handle uncertainty signals and routinely spike to 0.85+, while structural validation heads rarely exceed 0.5 even on malformed input. the problem is that most activation threshold research treats all heads in layer 28 as homogeneous which completely misses this specialization pattern