Oracle skyline — sentiment-shortcut ablation ceiling

SENTIMENT-shortcut experiment (bad / zxq cues; Qwen-0.5B & Llama-8B), not emergent misalignment. Scaled-up version of the oracle-search experiment: greedy eval-set search over a much larger candidate pool (800 unsigned / 400 per C± bucket, greedy curve to k≤80), maximizing worst-group accuracy. Compares the unsigned |grad×act| pool vs the signed C+/C− pool.

Skyline ceilings

cellpoolbase worstbest worstbest ksearched
llama_bad_allunsigned0.8780.8907380
llama_bad_allcpm0.8780.8821480
llama_zxq_allunsigned0.0440.104680
llama_zxq_allcpm0.0440.0562280
qwen_bad_allunsigned0.3320.5421180
qwen_bad_allcpm0.3320.5924080
qwen_zxq_allunsigned0.0320.032080
qwen_zxq_allcpm0.0320.0663680
More neurons helps, and C+/C− wins at scale: qwen_bad worst 0.332 → 0.592 @k=40 (cpm) vs 0.542 @k=11 (unsigned) — the signed pool reaches a higher ceiling when allowed more neurons. zxq stays immune (0.03→0.07–0.10) at every budget.

What are the skyline neurons? (Opus auto-interp)

Mostly not interpretable cue features — the gap-reducing neurons are overwhelmingly generic syntactic/positional units (function words, punctuation, clause/sentence boundaries, the start-of-sequence token), with only a minority carrying mild semantic flavor. The ceiling is reached by removing generic capacity, not a localized semantic shortcut circuit.

qwen_bad_all (48 skyline neurons):

llama_bad_all (73 skyline neurons):

qwen_zxq_all (36 skyline neurons):

llama_zxq_all (27 skyline neurons):