loss
loss: 8 implementations from 7 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 7 distinct outputs across 6 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:
- 5 more implementations of this name were examined but did not run on the shared input (RuntimeError 3, ValueError 2).
- 1 more implementation from 1 paper took no array argument and ran only on its own fixture arguments; no shared input existed for it, so it is not compared (on 1 the recorded shared-output digest is the own-fixture digest).
- Every compared output was digested.
Bucket 1 of 6: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 2, kind float, dtype float32
3 implementations 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); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 2 implementations 1 paper af5570f5a181 recorded values identical |
infinite_training_time.py 5c9c6003 recorded pred:2/float/float32, Y:2/float/float32 finite_training_time_convergence.py 9e75157a recorded pred:2/float/float32, Y:2/float/float32 |
[0] shape [] · float32 · Tensor |
| 1 implementation 1 paper 3e72399f4d4c |
shica/shicaj.py f7ebefe5 recorded D:2/float/float32, CY:2/float/float32 |
[179.959] shape [] · float64 |
Bucket 2 of 6: arg 1: rank 1, kind float, dtype float32 · arg 2: rank 1, 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper e37c9e3b518d |
test_func/run_toy.py 68cef691 recorded x:1/float/float32, y:1/float/float32 |
[7.78376] shape [] · float32 · Tensor |
Bucket 3 of 6: arg 1: rank 1, kind float, dtype float64 · arg 2: rank 1, kind float, dtype float64 · arg 3: rank 1, kind float, dtype float64
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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 8021914464b7 |
dmft.py ee4033ae recorded a:1/float/float64, h:1/float/float64, h_star:1/float/float64; symmetry='TEST' |
[1.46585] shape [] · float64 |
Bucket 4 of 6: arg 1: rank 1, kind float, dtype float64 · arg 2: rank 1, kind float, dtype float64
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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper f5a5fd42d16a |
examples/gromov/plot_gromov.py 68f28b95 recorded x:1/float/float64, y:1/float/float64 |
[0, 0, 0, 0, 0, 0, 0, 0] shape [8] · float64 · ndarray |
Bucket 5 of 6: arg 1: rank 2, 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 4775be33aff8 |
IQL.py 162c85e4 recorded diff:2/float/float32; expectile=0.8 |
[2.59958, 0.470494, 0.181301, 0.095465, 0.163027, 0.212374, 0.0878504, 0.262562, …] shape [4, 8] · float32 · Tensor |
Bucket 6 of 6: arg 1: rank 3, kind float, dtype float32 · arg 2: rank 3, 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 374708fff771 |
toy_experiment.py 7ccf5c55 recorded P:3/float/float32, target_P:3/float/float32 |
[0, 0] shape [2] · 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/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