{"as_of":"2026-08-22T05:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7a0c819217a42cc16395beb5526c365333985507e20a2677ed91679b41afa817","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T15:08:17.564427Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.02705/citation-record","integrity":"/paper/2608.02705/integrity","json":"/paper/2608.02705/citation-record.json","paper":"/paper/2608.02705"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.811417Z","title":"Accounting for variance in machine learning benchmarks","venue":null,"work_id":"fa899f81-a34d-40ea-a9b8-662f765dfb8b","year":2021},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.369374Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:1bc0ab9eab6ffcf1a455891f41e4d31c6baff08bca33b106748000cc6a519277","observation_id":"a7314d72-5e40-4e91-bc9c-4511d3a6446b","resolution":{"observed_at":"2026-08-15T15:08:17.815167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.374214Z","title":"Double/debiased machine learning for treatment and structural parameters","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.374214Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:deb068597a177c3740f8406600edff0f383e2cb1244b6f4223d19aa2064b883c","observation_id":"431c4d2d-9279-40d6-9b90-76e1c51cf924","resolution":{"observed_at":"2026-08-15T15:08:17.374214Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.07002","last_updated":"2021-07-14T21:08:30Z","snapshot_observed_at":"2026-08-19T06:03:25.160551Z","submitted_at":"2021-07-14T21:08:30Z","title":"The Benchmark Lottery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.07002","snapshot_observed_at":"2026-08-15T15:08:17.483421Z","title":"A., Zhao, Z., Houlsby, N., Diaz, F., Metzler, D., and Vinyals, O","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.483421Z"},"links":{"cited_paper":"/paper/2107.07002","citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:d1ea9ccbd3c5fb13b2924be2403e2684b93c0409f91958fe5f2f8a96874fda12","observation_id":"d3631de9-aa5b-4b24-ae9e-201c2c5e0a9e","resolution":{"observed_at":"2026-08-15T15:08:17.483421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.792660Z","title":"Improving the sensitivity of online controlled experiments by utilizing pre-experiment data","venue":null,"work_id":"1535305e-5ef8-4935-b926-7e9920c08494","year":2013},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.489647Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:9c47063b52871ceaf0be92ef63c8483d4d1205268e1fc8822079ac86b0d6a363","observation_id":"262e8b11-7353-48ea-a99d-bac4e43fa416","resolution":{"observed_at":"2026-08-15T15:08:17.796749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.06305","last_updated":"2020-02-15T02:40:10Z","snapshot_observed_at":"2026-08-12T00:45:25.809655Z","submitted_at":"2020-02-15T02:40:10Z","title":"Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.06305","snapshot_observed_at":"2026-08-15T15:08:17.493758Z","title":"Fine-tuning pretrained language models: Weight initializations, data orders, and early stopping","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.493758Z"},"links":{"cited_paper":"/paper/2002.06305","citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:ebaf81c6114d4b3e6f673ad422887311cf79bfa3d45dd9763d59fb1b5547abea","observation_id":"b4e97a7e-b0fe-44af-9d9e-2dfd72fd626e","resolution":{"observed_at":"2026-08-15T15:08:17.493758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.781111Z","title":"T., and Hutter, F","venue":null,"work_id":"67725d03-b23c-48b1-ab7d-8bc667beceb9","year":2015},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.499324Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:3433a48faa5f3d9b6f911db1209575a56564535ffaa52c9801a18c240c4b3e06","observation_id":"9f5b5d49-38af-40cf-83ad-1c6163e6c0c9","resolution":{"observed_at":"2026-08-15T15:08:17.785478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.769245Z","title":null,"venue":null,"work_id":"8f4911ca-6946-4f2c-8de6-0d282a2fcf6c","year":2008},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.503411Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:524a66807bbd65aa04c7fbe3977b86ee237267bc888d9f266d847e730163929c","observation_id":"0c7d61f0-1950-4f19-939e-10999a7412ae","resolution":{"observed_at":"2026-08-15T15:08:17.772904Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.757068Z","title":"B., Stern, H","venue":null,"work_id":"03d1efc2-dd5d-40e3-a6a2-d7c1e6dbfec9","year":2013},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.507217Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:86ba12dfa84db600b18a65ec39a93eab0da80df030697a53a2ac713ac23f3d8f","observation_id":"0d4f0bb0-7ae8-4578-932f-88c87d52e37a","resolution":{"observed_at":"2026-08-15T15:08:17.761384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.511988Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.511988Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:93b8264fc4b09b59ba850ea7975d08edf11b395d90f9ea1098d7a580cca3b99e","observation_id":"26682572-b5a5-4782-a14f-6d0cba72a9cd","resolution":{"observed_at":"2026-08-15T15:08:17.511988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.737773Z","title":"Deep reinforcement learning that matters","venue":null,"work_id":"76729382-3938-47ae-b9c9-f15533964894","year":2018},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.516099Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:4391bf889348cccbfc06326c333b2d7cac7b14447a0e6bc35f432ecde8194192","observation_id":"9f509845-47a0-4a56-a6a9-8ea977350fd5","resolution":{"observed_at":"2026-08-15T15:08:17.742262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.726574Z","title":"Always valid inference: Continuous monitoring of a/b tests","venue":null,"work_id":"ca4becec-a7e9-4aac-afd8-fb982bd42fa1","year":2022},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.519797Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:cd6a161c1c7eec19297472b2e0c051a81eacf45580809be8ae1eb2a83a4db5aa","observation_id":"91f1b06c-cdec-42e6-8309-8584ebaee754","resolution":{"observed_at":"2026-08-15T15:08:17.730466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.523342Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.523342Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:b208dce8d5cf6e75a4b75d0b73fcbacd15de0f55e665c84e6976e16c7e9159ce","observation_id":"abf17315-e7db-4620-88b7-e96e5bd96c37","resolution":{"observed_at":"2026-08-15T15:08:17.523342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.527875Z","title":"and Yang, X","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.527875Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:bd0894f51292761776c5332b7aecc9ba1b103de420bf4f43b630e63ff38babc4","observation_id":"30cc85a8-f350-4513-a53e-ae2bd9e97c25","resolution":{"observed_at":"2026-08-15T15:08:17.527875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.700901Z","title":"Agnostic notes on regression adjustments to experimental data: R eexamining F reedman's critique","venue":null,"work_id":"4866f10b-95b2-46f0-ab19-6541c4edaad5","year":2013},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.531966Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:00c48851c0c3013e200fa21ee82bfd4ac3f72b3950dddf29b6b980a911dd18f3","observation_id":"20933144-8ae6-4d2a-abb3-200c6ee6f3e4","resolution":{"observed_at":"2026-08-15T15:08:17.705023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.536101Z","title":"A ConvNet for the 2020s","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.536101Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:3ffcffab5b94440c7d7dd477fd2570e0873cbd8f39316dd9af98df1bf6f1b035","observation_id":"0e5a29dd-483c-4efb-86da-5742944c338a","resolution":{"observed_at":"2026-08-15T15:08:17.536101Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.682242Z","title":"Are GAN s created equal? A large-scale study","venue":null,"work_id":"195bc83f-fc93-41bb-82ac-e2740c1948a4","year":2018},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.540063Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:22926acc23e5334bf7ff0b909ebfddfec0d69165ca463483ed7627d7b5074b74","observation_id":"387ffecd-2484-4831-8840-4c03b3315c20","resolution":{"observed_at":"2026-08-15T15:08:17.686326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.670800Z","title":null,"venue":null,"work_id":"d3b5eab6-334e-497c-a7f3-55462d4eeb05","year":2013},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.543652Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:85e573586ca7af5f3bc50002e1cf1c07fbb0a50037cbf79ef31d29138dfb80de","observation_id":"f299f6c0-0317-478f-b460-bd4f163b195d","resolution":{"observed_at":"2026-08-15T15:08:17.674499Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.08203","last_updated":"2023-05-11T21:36:07Z","snapshot_observed_at":"2026-08-18T04:23:48.744459Z","submitted_at":"2021-09-16T20:10:12Z","title":"Torch.manual_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.08203","snapshot_observed_at":"2026-08-15T15:08:17.548073Z","title":"Torch.manual\\_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.548073Z"},"links":{"cited_paper":"/paper/2109.08203","citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:4b6f412b2708debc03d6f50d48229358c60720013eef64337ca8ce421230e9df","observation_id":"3729fe4c-43b0-49b3-bb3f-79672664f8a0","resolution":{"observed_at":"2026-08-15T15:08:17.548073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.658536Z","title":"Boosted decision tree regression adjustment for variance reduction in online controlled experiments","venue":null,"work_id":"356e62dc-8967-4cf0-9bf4-e5855a7ebda3","year":2016},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.552512Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:3bbdccd7d9912d0e8f5d3023535cf7e3081d8c599bb5574865ab0573c1275346","observation_id":"678f1b4e-d25c-4b0e-a90d-15b89d8c13de","resolution":{"observed_at":"2026-08-15T15:08:17.662742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.646979Z","title":null,"venue":null,"work_id":"e38ad2bf-c031-483f-b749-0baad399242c","year":1984},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.556736Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:6949b6d42e6c9e94186cbb8c2f7c30885ee64055442a8434fa9e842f41076225","observation_id":"82797e3d-1705-4640-b03d-a8e5d29058ce","resolution":{"observed_at":"2026-08-15T15:08:17.651118Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.634484Z","title":"R., Eisenstein, J., Das, D., and Pavlick, E","venue":null,"work_id":"ea933f15-87bc-4ad7-ba32-49896a2e9c4b","year":2022},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.560986Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:7c8825149ba6d158fdd6a311fb4c9a4f87c379aecd60364f4794e2e4d5be69b3","observation_id":"7ff24d29-afbe-4ddf-90fd-ce5f7d640b21","resolution":{"observed_at":"2026-08-15T15:08:17.638212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:08:17.619725Z","title":"Training data-efficient image transformers & distillation through attention","venue":null,"work_id":"1703374f-25ea-4f43-bafb-a54979c8ee6b","year":2021},"citing_paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:17.564427Z"},"links":{"citing_paper":"/paper/2608.02705"},"observation_digest":"sha256:25c9ebb4bfdfa57d2f6df371de6a4595d7c83a365fe0f4021b9d8f1cf6fa79cf","observation_id":"0c739aec-c1be-4e48-81a0-a5442d2d5912","resolution":{"observed_at":"2026-08-15T15:08:17.626204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.02705","last_updated":"2026-08-03T16:08:14Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-21T18:41:04.047630Z","submitted_at":"2026-08-03T16:08:14Z","title":"Can Training Logs Make Model Comparisons More Precise?"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":22},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2608.02705."}