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l1_loss

Syntologyfunction-name censuscensus 2026-09-22battery b986f7e04d79all samples with this name

l1_loss: 3 implementations from 7 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 3 distinct outputs across 3 buckets, one shared input per bucket.

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence. Implementations are compared only within one bucket, the positional (rank, kind, dtype) of each array argument; the argument name is not part of the key because the harness draws the shared array from (rank, kind) and casts it to the dtype, whatever the name; each bucket's shared input is fixed by that key, so members of one bucket saw bitwise-identical inputs under their own scalar arguments. A cluster is the set of members whose recorded output digest is identical. Nothing here says which computation a paper's method intended, and nothing reproduces a paper's results.

Not compared, and not in the tables or the counts above:

Bucket 1 of 3: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 2, kind float, dtype float32

1 implementation from 4 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
4 papers
5341e6b26469
one code sha held from 4 papers' repositories
zoobot/pytorch/training/finetune.py 5c7e0fe9
recorded y_pred:2/float/float32, y:2/float/float32
[0, 0, 0, 0, 0, 0, 0, 0, …]
shape [4, 8] · float32 · Tensor

Bucket 2 of 3: arg 1: rank 2, kind float, dtype float32

1 implementation from 2 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
2 papers
96e4b56fcb18
one code sha held from 2 papers' repositories
detection/GroupFree3D/models/loss_helper.py e1e4a142
recorded error:2/float/float32
[1.80263, 1.53378, 0.476053, 0.690887, 0.902849, 1.03047, 0.662761, 0.572889, …]
shape [4, 8] · float32 · Tensor

Bucket 3 of 3: arg 1: rank 4, kind float, dtype float32

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
24754a2ee285

generation/dps.py e90ea3b7
recorded x:4/float/float32; n_obs=2
[6.33223, 5.87988, 5.94477, 8.85038, 6.41051, 6.98117]
shape [2, 3] · float32 · Tensor

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence; where a cluster's members carry recorded values, the largest difference among them is shown under the cluster. Paper titles are the archive's archive 2025-07-28 where the paper is in the archive and the graph's where it was added by Syntology; papers with no page here are shown by their recorded paper id only. A paper count above the implementation count means one implementation (one code sha) is held from several papers' repositories and counts once. Per-sample status, licence and fingerprint records for each paper are on its paper page. JSON twin: /census/l1-loss.json.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections