ECHO Benchmark

ECHO-Synth

Graph Regression

Mixed graph/node regression suite covering diameter (graph-level), eccentricity (node-level), and SSSP (node-level) on synthetic long-range graphs. Inputs expose only local graph state while targets require long-range information. Evaluated by MAE.

Dataset details

Task

ECHO synthetic propagation task — node-level regression on synthetic long-range graphs. The primary catalog metric is MAE.

Data

ECHO synthetic propagation task — node-level regression on synthetic long-range graphs. The cataloged artifact reports 10,080 graphs.

Features

Each synthetic or physical graph supplies local node/edge state and a target created by controlled long-range propagation. The exact signal channels and propagation parameters are part of the named ECHO task and should not be mixed across variants.

Splits and evaluation

The catalog records these protocols or variants: Standard split. Evaluation uses MAE (lower is better). Exact masks or folds must come from the cited release.

Quirks and pitfalls

Performance is sensitive to propagation radius, graph size, and train/test distance regime. Randomly mixing configurations can turn a long-range extrapolation task into interpolation; report the named variant and fixed generation parameters.

Sources

SOTA Progression

new SOTA matches SOTA at that time other proposed result other baseline result

Leaderboard

#ModelMAE ↓Paper
1
GHR
0.0350 ± 0.0040
2
GRIT
0.1210 ± 0.0130
3
GHR-GINE
0.3790 ± 0.1910
4
GPS
0.4720 ± 0.0500
5
SWAN
0.8960 ± 0.2320
6
A-DGN
1.1510 ± 0.0380
7
DRew
1.2430 ± 0.0470
8
PH-DGN
1.3230 ± 0.4850
9
GIN/GINE
1.6300 ± 0.1610
10
GIN
1.6300 ± 0.1610
11
GCNII
2.0050 ± 0.0930
12
GCN
2.1020 ± 0.0940
13
GraphCON
2.9690 ± 0.1890
SOTA performance set a new SOTA at the time matched the SOTA at the time