Paper 2 · per-game results

Private Eye

The exact ground truth for this ROM and how every interpretability method scores against it — one of the 44 scored games. Every number is read from site_data.json (games.private_eye).

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Private Eye screen

Ground truth

External label source
AtariARI + OCAtari
Verified causal labels
12
Labels that move a sprite
10
Scorable (enough true causes)
yes
Position regime
yes — a moving tracked sprite at this frame

The screenshot is the exact analysis frame the ground truth is computed on. Labels are imported (AtariARI / OCAtari) then verified causally on the bit-exact machine.

Every method's faithfulness on Private Eye

Each XAI / mechanistic-interpretability method's faithfulness on this ROM, sorted by F (click a header to re-sort). The left border marks the tradition: green = causal / intervention, red = gradient / correlational, amber = other — the split the paper's headline turns on. F is all-regime; content-F and position-F are the two output regimes (n/a where this game has no record for that regime).

MethodFamilyF (all)content-Fposition-FSM
A2 · Single-unit lesionscausal / intervention1.000n/an/a0.6111.000
A8 · Whole-state recordingdescriptive1.000n/an/a1.0000.094
Activation patching / causal mediationcausal / intervention1.000n/a1.0001.0001.000
Interchange interventions / DAScausal / intervention1.000n/an/a1.0000.917
Causal scrubbingcausal / intervention0.890n/an/a0.8900.818
Logit / tuned lenscausal / intervention0.877n/an/an/a0.275
Occlusioncausal / intervention0.7480.7580.7390.9601.000
LIMEgradient / correlational0.7340.7310.7370.9600.229
RISEgradient / correlational0.7180.7130.7230.9600.230
On-distribution counterfactualcausal / intervention0.6340.7580.5100.9601.000
KernelSHAP / Shapleygradient / correlational0.6200.5030.7370.9600.229
A7 · Dimensionality reduction (NMF/PCA)dim_reduction0.600n/an/an/an/a
Attribution / edge patchinggradient / correlational0.497n/an/a0.9541.000
Grad×Input / DeepLIFTgradient / correlational0.4870.9700.0030.9601.000
A5 · Local field potentialsgradient / correlational0.458n/an/an/an/a
Expected Gradientsgradient / correlational0.3800.7580.0030.9601.000
Integrated Gradientsgradient / correlational0.3800.7580.0030.9601.000
Vanilla gradient (saliency)gradient / correlational0.3800.7580.0030.9601.000
SmoothGradgradient / correlational0.3800.7580.0030.9601.000
Guided Backpropgradient / correlational0.3790.7580.0000.9601.000
A1 · Connectomics / data-flow graphcausal / intervention0.364n/an/a1.0001.000
ACDC — automatic circuit discoverycausal / intervention0.364n/an/a0.1671.000
Extremal / meaningful perturbationcausal / intervention0.3470.5070.1880.9601.000
NMF/PCA dictionariesdim_reduction0.291n/an/a0.9991.000
Path patching / IOI circuitcausal / intervention0.222n/an/an/a1.000
A3 · Tuning curvesgradient / correlational0.166n/an/a0.2921.000
Sparse autoencodersdim_reduction0.118n/an/a0.0661.000
A6 · Granger causalitygradient / correlational0.100n/an/a0.9800.818
Linear probing + control tasksprobing0.088n/an/an/a1.000
A4 · Pairwise correlationsgradient / correlational0.011n/an/a0.1200.321

Source: site_data.json · generated by gen_site_data.py from the committed §R records + leaderboard.json.