Paper 2 · per-game results

Pitfall

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.pitfall).

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Pitfall screen

Ground truth

External label source
AtariARI + OCAtari
Verified causal labels
10
Labels that move a sprite
8
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 Pitfall

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/a0.9171.000
A8 · Whole-state recordingdescriptive1.000n/an/a1.0000.086
Activation patching / causal mediationcausal / intervention1.000n/a1.0001.0001.000
Causal scrubbingcausal / intervention1.000n/an/a1.0000.667
Interchange interventions / DAScausal / intervention1.000n/an/a1.0000.923
Attribution / edge patchinggradient / correlational0.783n/an/a0.9181.000
Occlusioncausal / intervention0.7350.7520.7170.8820.875
LIMEgradient / correlational0.7000.6930.7060.8820.344
KernelSHAP / Shapleygradient / correlational0.6970.6860.7070.8820.344
RISEgradient / correlational0.6010.5520.6490.8820.344
Grad×Input / DeepLIFTgradient / correlational0.4980.9970.0000.9121.000
Logit / tuned lenscausal / intervention0.458n/an/an/a0.104
On-distribution counterfactualcausal / intervention0.4340.5450.3230.9411.000
A5 · Local field potentialsgradient / correlational0.415n/an/an/an/a
A7 · Dimensionality reduction (NMF/PCA)dim_reduction0.400n/an/an/an/a
A4 · Pairwise correlationsgradient / correlational0.345n/an/a0.3350.141
Extremal / meaningful perturbationcausal / intervention0.3260.4790.1730.8820.875
A1 · Connectomics / data-flow graphcausal / intervention0.308n/an/a0.9751.000
ACDC — automatic circuit discoverycausal / intervention0.308n/an/a0.4381.000
NMF/PCA dictionariesdim_reduction0.203n/an/a0.9671.000
Linear probing + control tasksprobing0.184n/an/an/a1.000
A3 · Tuning curvesgradient / correlational0.146n/an/a0.2570.846
A6 · Granger causalitygradient / correlational0.000n/an/a0.9120.846
Expected Gradientsgradient / correlational0.0000.0000.0000.8821.000
Guided Backpropgradient / correlational0.0000.0000.0000.8821.000
Integrated Gradientsgradient / correlational0.0000.0000.0000.8821.000
Path patching / IOI circuitcausal / intervention0.000n/an/an/an/a
Sparse autoencodersdim_reduction0.000n/an/a-0.2480.846
Vanilla gradient (saliency)gradient / correlational0.0000.0000.0000.8821.000
SmoothGradgradient / correlational0.0000.0000.0000.8821.000

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