Home › Census › sample

sample

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

sample: 8 implementations from 9 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 7 distinct outputs across 5 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 5: arg 1: rank 3, kind float, dtype float32

3 implementations 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); 2 distinct outputs, 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
2 implementations
3 papers
fa99eb14cf3d
recorded values identical
one code sha held from 2 papers' repositories
angelslim/compressor/speculative/train/models/draft/qwen_dflare.py ab21ebd9
recorded logits:3/float/float32; temperature=0.8

tree_flash.py 12b15cc8
recorded logits:3/float/float32; temperature=0.8
[1, 4, 0, 5, 1, 7, 4, 2]
shape [2, 4] · int64 · Tensor
1 implementation
1 paper
53781a550edb

diffusion.py 06448db9
recorded scores:3/float/float32; N=5, deterministic=False
[1, 7, 6, 4, 0, 5, 3, 2, …]
shape [5, 2, 4, 8] · int64 · Tensor

Bucket 2 of 5: arg 1: rank 2, kind float, dtype float32

2 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)MembersShared output on this bucket's input
1 implementation
1 paper
01ba64c03421
  • arXiv:2507.12000

results/distribute_sp.py a2d0fabb
recorded logits:2/float/float32; temperature=1.0, top_k=0, top_p=0.0
[7, 5, 6, 5]
shape [4, 1] · int64 · Tensor
1 implementation
1 paper
5f7a4d906bc1

ccil/intervention_policy_execution.py dfb4cca4
recorded weights:2/float/float32; temperature=1.5
[1, 0, 1, 1, 1, 0, 0, 0, …]
shape [4, 8] · int64 · ndarray

Bucket 3 of 5: 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)MembersShared output on this bucket's input
1 implementation
1 paper
de2a7bfc268a

src/train_ace.py 0962a70b
recorded target:1/float/float32, unconditional:1/float/float32; sampling_batch_size=2, tokenizer=None, text_encoder=None
[-0.903889, 0.157131, 0.897612, -0.762196, -0.176256, 0.0530317, -1.62844, -0.177533, …]
shape [32] · float32 · Tensor

Bucket 4 of 5: arg 1: 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)MembersShared output on this bucket's input
1 implementation
1 paper
05264cc120d9

tester.py dcdd0b5c
recorded x:1/float/float64
[-0.841706]
shape [] · float64

Bucket 5 of 5: arg 1: rank 4, kind float, dtype float32 · arg 2: 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)MembersShared output on this bucket's input
1 implementation
1 paper
a6b3aaaaad3f

inference.py 21949a5a
recorded dec_img:4/float/float32, extra_cond:2/float/float32; net=Net( (linear): Linear(in_features=6, out_features=8, bias=, encoder=Encoder( (linear): Linear(in_features=5, out_features=6, b, img_size=64
[0.446243, 0.322447, 0.637082, 0.564545, 0.456619, 0.336541, 0.718748, 0.61984, …]
shape [4, 3, 4, 4] · 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/sample.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