{"as_of":"2026-08-20T13:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:88584d4deb2b04efe4d31b312ff85e588bfd1cd5bea9c77f21bca5c4e4cd6719","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:42:03.731235Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T18:45:52.380042Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-09T06:15:37.236583Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"cited_work":{"arxiv_id":"2506.13216","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.13216","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2506.13216 , year=","venue":null,"work_id":"87de1bca-8023-4e10-ae67-1e5dd491b05d","year":null},"citing_paper":{"arxiv_id":"2605.02364","last_updated":"2026-05-04T09:07:54Z","snapshot_observed_at":"2026-08-17T17:54:48.124462Z","submitted_at":"2026-05-04T09:07:54Z","title":"InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-05-08T18:45:52.380042Z"},"links":{"cited_paper":"/paper/2506.13216","citing_paper":"/paper/2605.02364"},"observation_digest":"sha256:191d2dc36be149f8cb770ff33f27a95fa1fff237540e41216ad5a6ad2553e27f","observation_id":"9e7d1f0a-44e0-42cb-82f6-574c6dd46af9","resolution":{"observed_at":"2026-05-09T06:15:37.238284Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.13216/citation-record","integrity":"/paper/2506.13216/integrity","json":"/paper/2506.13216/citation-record.json","paper":"/paper/2506.13216"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.15936","last_updated":"2023-11-06T00:36:24Z","snapshot_observed_at":"2026-08-16T22:55:19.544394Z","submitted_at":"2023-07-29T09:22:54Z","title":"A Theory for Emergence of Complex Skills in Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15936","snapshot_observed_at":"2026-08-07T00:41:59.813968Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T00:41:59.813968Z"},"links":{"cited_paper":"/paper/2307.15936","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:43f456aedaf6d37ad6c1dc4b4dc447917a17bbb4ed40c5c86f9a3ebcabf7aed1","observation_id":"47352f9c-cfd1-471a-89fa-c9625f79d6e3","resolution":{"observed_at":"2026-08-07T00:41:59.813968Z","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":"2026-08-07T00:42:05.237259Z","title":null,"venue":null,"work_id":"e02bf9a5-eab1-41db-b8a1-1b6008ef41cc","year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T00:41:59.850459Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:a13edf2bf2103a0b6d90b9a63f126c72b62e22540e34234001dfcb961641bc15","observation_id":"4e890e31-a817-4159-bae8-b3921f9c860e","resolution":{"observed_at":"2026-08-07T00:42:05.306194Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16609","last_updated":"2023-09-28T17:07:49Z","snapshot_observed_at":"2026-08-09T21:25:20.369782Z","submitted_at":"2023-09-28T17:07:49Z","title":"Qwen Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16609","snapshot_observed_at":"2026-08-07T00:41:59.909257Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T00:41:59.909257Z"},"links":{"cited_paper":"/paper/2309.16609","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:c61af8ada7f1cbaf0fe5ec1bfdafa470188bf054c3808145c99e45ca59fbc3ef","observation_id":"11ec7c3a-b7f9-4d54-bdde-1f917093e875","resolution":{"observed_at":"2026-08-07T00:41:59.909257Z","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":"2026-08-07T00:41:59.998753Z","title":null,"venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T00:41:59.998753Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:fe2a30174adb29aaad95d73edd8f53e2ecad43c8be2727da0143774f9e8c4f05","observation_id":"25fc96ec-49df-4f03-be97-f2646bfa24e9","resolution":{"observed_at":"2026-08-07T00:41:59.998753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.17297","last_updated":"2024-03-26T00:53:24Z","snapshot_observed_at":"2026-08-12T16:46:46.561976Z","submitted_at":"2024-03-26T00:53:24Z","title":"InternLM2 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.17297","snapshot_observed_at":"2026-08-07T00:42:00.044321Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.044321Z"},"links":{"cited_paper":"/paper/2403.17297","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:2010933b344c68372d031860cee6421afb514a5e915cac6bedd089ce23d208f7","observation_id":"7079b3dd-8e63-47e1-9d05-6742a27e85b7","resolution":{"observed_at":"2026-08-07T00:42:00.044321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T00:42:00.134273Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.134273Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:e3c55c0fa33ba1878135cc7cda2d936a7456711147eb0c316ac9c7b4ba52b28f","observation_id":"f2aa446d-f0bc-4cca-94e7-dd482663ea6f","resolution":{"observed_at":"2026-08-07T00:42:00.134273Z","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":"2026-08-07T00:42:00.178877Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.178877Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:d33f25571a12230ab470db1436d95fe368b528a8cbc4cf259c6e3a91dd776a6d","observation_id":"5b3bc751-9f18-48be-84e9-3321172e30f3","resolution":{"observed_at":"2026-08-07T00:42:00.178877Z","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":"2026-08-07T00:42:00.235628Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.235628Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:46ecb79154ebf4808f2f29332b66ade822599dd6e3302aaafaea5843a2fa9fb7","observation_id":"6bfdbe2c-2e2a-4e3f-999c-51fd69d932cc","resolution":{"observed_at":"2026-08-07T00:42:00.235628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.15796","last_updated":"2025-01-15T02:48:59Z","snapshot_observed_at":"2026-08-16T14:07:07.590212Z","submitted_at":"2024-03-23T11:03:31Z","title":"Understanding Emergent Abilities of Language Models from the Loss Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.15796","snapshot_observed_at":"2026-08-07T00:42:00.296033Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.296033Z"},"links":{"cited_paper":"/paper/2403.15796","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:1b731d2d4fa7d68a39089f335409228757eb2eadebeb0a6771ca5b0fa47174db","observation_id":"8dae9bd0-9a5c-419a-ba21-37e4a47687ba","resolution":{"observed_at":"2026-08-07T00:42:00.296033Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T00:42:00.355514Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.355514Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:feac318dafef307547a68c08da6546677798f9b412a9a6f0c953b267f45ccee7","observation_id":"dec9ba48-7f58-444a-9747-8a5abd389b97","resolution":{"observed_at":"2026-08-07T00:42:00.355514Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.08540","last_updated":"2024-06-14T20:21:05Z","snapshot_observed_at":"2026-08-16T14:10:11.362149Z","submitted_at":"2024-03-13T13:54:00Z","title":"Language models scale reliably with over-training and on downstream tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.08540","snapshot_observed_at":"2026-08-07T00:42:00.412605Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.412605Z"},"links":{"cited_paper":"/paper/2403.08540","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f360518e74060d4844f83f03fb1756f77f4d39852f74b11151eea4d861d2fcec","observation_id":"b28c3092-7bbd-410f-bb9d-c04b4d123d55","resolution":{"observed_at":"2026-08-07T00:42:00.412605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.03300","last_updated":"2021-01-12T18:57:11Z","snapshot_observed_at":"2026-08-13T20:44:28.824685Z","submitted_at":"2020-09-07T17:59:25Z","title":"Measuring Massive Multitask Language Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.03300","snapshot_observed_at":"2026-08-07T00:42:00.507815Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.507815Z"},"links":{"cited_paper":"/paper/2009.03300","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:8aac5abdf9b4fccdc81a6c8ebced5a5b7c2a539dd4664cdcec05df99cc7adc28","observation_id":"07cf7857-0943-4575-b603-7eebe0d0dd09","resolution":{"observed_at":"2026-08-07T00:42:00.507815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-08-09T19:52:33.533277Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-07T00:42:00.563289Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.563289Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:851281388f1769ee29cce3d68325f6afea0a844ebf565055ef7703c9d0da1ea0","observation_id":"ab77f60b-801c-4009-b756-ae7a5a76be65","resolution":{"observed_at":"2026-08-07T00:42:00.563289Z","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":"2026-08-07T00:42:05.055337Z","title":null,"venue":null,"work_id":"8851158a-561f-47bb-b451-b9e88c7896b3","year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.614069Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:bb1a212e4b8e7ec36a1f50a3ae087c2a3ff0143c5e8c788723c4f0164a3166a9","observation_id":"2efbe2d0-ff55-47a2-a639-3a4fd5af98ca","resolution":{"observed_at":"2026-08-07T00:42:05.171014Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-07T00:42:00.668869Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.668869Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:a2858488f4ce0de513e2ec1a02e6e59aa38031d668066d5a38de873fc86ea70f","observation_id":"eda7acf7-2a28-433b-be37-2cafb4ae7ef0","resolution":{"observed_at":"2026-08-07T00:42:00.668869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-07T00:42:00.722581Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.722581Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:88b28f295dccfa79fa5e7a08916d18e63f9705ff15bee9d13ce29fc0e954d0f0","observation_id":"52e2baaf-c097-4b6c-b8e1-ead68812d88d","resolution":{"observed_at":"2026-08-07T00:42:00.722581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12844","last_updated":"2025-02-20T16:20:11Z","snapshot_observed_at":"2026-08-16T13:36:58.590002Z","submitted_at":"2024-07-04T17:57:38Z","title":"metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12844","snapshot_observed_at":"2026-08-07T00:42:00.775227Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.775227Z"},"links":{"cited_paper":"/paper/2407.12844","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:9f5fac1b1f978401c2a5b360462bcd663564a6f343d0d6338b6d04eccde5edf2","observation_id":"3d6133d1-c2e2-4143-8d7f-6fd5889bdb46","resolution":{"observed_at":"2026-08-07T00:42:00.775227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09212","last_updated":"2024-01-17T19:09:57Z","snapshot_observed_at":"2026-08-04T18:52:19.083847Z","submitted_at":"2023-06-15T15:49:51Z","title":"CMMLU: Measuring massive multitask language understanding in Chinese","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09212","snapshot_observed_at":"2026-08-07T00:42:00.856511Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.856511Z"},"links":{"cited_paper":"/paper/2306.09212","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:019bcffbe4acf92ca8487899e2022032c2e8f98fd24f383289f65a219192ba54","observation_id":"9720c97c-b729-4721-a50b-7b2d3595864e","resolution":{"observed_at":"2026-08-07T00:42:00.856511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09110","last_updated":"2023-10-01T21:44:23Z","snapshot_observed_at":"2026-08-10T23:10:13.900680Z","submitted_at":"2022-11-16T18:51:34Z","title":"Holistic Evaluation of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09110","snapshot_observed_at":"2026-08-07T00:42:00.924943Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.924943Z"},"links":{"cited_paper":"/paper/2211.09110","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:25196c7f0cfede5c11ce0299eb8f2bb45334537a2445ffd74bb9dbc7cd6dbe6a","observation_id":"3a9f4759-c3dc-40ae-b1c3-776290aa4053","resolution":{"observed_at":"2026-08-07T00:42:00.924943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07965","last_updated":"2025-01-08T09:07:54Z","snapshot_observed_at":"2026-08-19T08:13:57.917283Z","submitted_at":"2024-04-11T17:52:01Z","title":"Rho-1: Not All Tokens Are What You Need","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07965","snapshot_observed_at":"2026-08-07T00:42:00.976666Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:00.976666Z"},"links":{"cited_paper":"/paper/2404.07965","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:70ff875e14778a4af2b44a1419a38e50d7461d9ae08c83ee8e0c164d72f706c3","observation_id":"7bba15c1-ce11-4a95-b04b-30fe549d7e98","resolution":{"observed_at":"2026-08-07T00:42:00.976666Z","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":"2026-08-07T00:42:04.815780Z","title":null,"venue":null,"work_id":"4c78b85b-dacc-40c5-bbad-5a7f3944910c","year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.051069Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:6282c8ebed4b430fc48a185af304e6fb8a6969a9811885f6b84831b7a4e96289","observation_id":"e9e6578f-d4ed-40ce-9ac3-1696843d68e1","resolution":{"observed_at":"2026-08-07T00:42:04.948236Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-07T00:42:04.656107Z","title":null,"venue":null,"work_id":"d3146c59-090f-47bc-9a5e-ad29dd897c53","year":2008},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.186499Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f9895c40c83bc1dc8d16dae2c18eafa485054dcae9fa5b854a368611849288ce","observation_id":"58a8ccf9-add8-4a51-8a2c-a60c51a1c070","resolution":{"observed_at":"2026-08-07T00:42:04.737140Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-07T00:42:01.293638Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.293638Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:6f9edc29a8d94dd937f8dee2990c0f956f99a7e7760ed309a9419b7b7b81ed20","observation_id":"58f4697f-35f3-479a-8a8a-6028b9f01fd9","resolution":{"observed_at":"2026-08-07T00:42:01.293638Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04757","last_updated":"2024-01-09T17:34:30Z","snapshot_observed_at":"2026-08-16T14:28:44.947758Z","submitted_at":"2024-01-09T17:34:30Z","title":"How predictable is language model benchmark performance?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04757","snapshot_observed_at":"2026-08-07T00:42:01.341630Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.341630Z"},"links":{"cited_paper":"/paper/2401.04757","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f60aa468c7d22fd8d307fa56dbd326297208a385513f0585962c625560b47d75","observation_id":"40fd6055-0c1d-4a1c-bcc0-0685509ffc0b","resolution":{"observed_at":"2026-08-07T00:42:01.341630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.03563","last_updated":"2024-09-05T14:19:45Z","snapshot_observed_at":"2026-08-16T13:21:03.297429Z","submitted_at":"2024-09-05T14:19:45Z","title":"100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.03563","snapshot_observed_at":"2026-08-07T00:42:01.431425Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.431425Z"},"links":{"cited_paper":"/paper/2409.03563","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:178cb3c30b22ea14e4ddcf2b2a6ef5d419e3638845f2eea0cbb4e6717eeebfd0","observation_id":"c101de66-854a-412a-97a9-21b2d6f251a1","resolution":{"observed_at":"2026-08-07T00:42:01.431425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11696","last_updated":"2024-04-01T17:34:34Z","snapshot_observed_at":"2026-08-20T05:38:28.460864Z","submitted_at":"2023-08-22T17:59:30Z","title":"Efficient Benchmarking of Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11696","snapshot_observed_at":"2026-08-07T00:42:01.663487Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.663487Z"},"links":{"cited_paper":"/paper/2308.11696","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:1b57714d3d86fc497671aec6f2823bf86ddc4f200e8e1708f365985e886f841c","observation_id":"a20a6729-266d-4ba0-812b-bb669541417c","resolution":{"observed_at":"2026-08-07T00:42:01.663487Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14992","last_updated":"2024-05-26T22:27:23Z","snapshot_observed_at":"2026-08-17T02:59:38.954198Z","submitted_at":"2024-02-22T22:05:23Z","title":"tinyBenchmarks: evaluating LLMs with fewer examples","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14992","snapshot_observed_at":"2026-08-07T00:42:01.796039Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.796039Z"},"links":{"cited_paper":"/paper/2402.14992","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:a3a08e97e2c15cdbaaa5be41929ed7c3b5e15449a60faeb10395ddbfc5661b65","observation_id":"d59413fb-5a76-4f9d-9122-6bf1fde6b3a1","resolution":{"observed_at":"2026-08-07T00:42:01.796039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.10938","last_updated":"2024-10-01T23:38:10Z","snapshot_observed_at":"2026-08-16T13:51:47.687448Z","submitted_at":"2024-05-17T17:49:44Z","title":"Observational Scaling Laws and the Predictability of Language Model Performance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.10938","snapshot_observed_at":"2026-08-07T00:42:01.938683Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:01.938683Z"},"links":{"cited_paper":"/paper/2405.10938","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:a460a713554e33680c07e7a9120406283e40cf7947fa8e52db7526662b96dbf7","observation_id":"c005dc66-f098-46ca-9697-9dbc9d6651ed","resolution":{"observed_at":"2026-08-07T00:42:01.938683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.04615","last_updated":"2023-06-12T17:51:15Z","snapshot_observed_at":"2026-07-06T13:19:12.109592Z","submitted_at":"2022-06-09T17:05:34Z","title":"Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.04615","snapshot_observed_at":"2026-08-07T00:42:02.070082Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.070082Z"},"links":{"cited_paper":"/paper/2206.04615","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f640bb0c4436d27bf6b4a4ac9dfb93857d405c9b0266db1401836958ac9ea8ff","observation_id":"a895cd9e-67aa-47a6-a767-fa403577897d","resolution":{"observed_at":"2026-08-07T00:42:02.070082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.09261","last_updated":"2022-10-17T17:08:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-17T17:08:26Z","title":"Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.09261","snapshot_observed_at":"2026-08-07T00:42:02.236382Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.236382Z"},"links":{"cited_paper":"/paper/2210.09261","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:7ff5922357e964725bdbe8530d0975ee682231ea9d32560fc003dd0806dffb55","observation_id":"6cac282e-53c0-4bbb-bb95-a84a01279c5f","resolution":{"observed_at":"2026-08-07T00:42:02.236382Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-07T00:42:02.352884Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.352884Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f35db3c2c6ed8504792d28226f165485a3b4224388075853d84a0ad06afefa07","observation_id":"37485b41-ca59-4384-8f7f-01f153b5156e","resolution":{"observed_at":"2026-08-07T00:42:02.352884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-07T00:42:02.553800Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.553800Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:cb0154c2414763226214a272c6c78bb96456956841a5cb15776017dce70ec01a","observation_id":"6fa9abe8-9111-46d4-bf28-e193f6343930","resolution":{"observed_at":"2026-08-07T00:42:02.553800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.09803","last_updated":"2023-05-30T03:33:27Z","snapshot_observed_at":"2026-08-18T16:32:58.678442Z","submitted_at":"2022-12-19T19:16:29Z","title":"Training Trajectories of Language Models Across Scales","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.09803","snapshot_observed_at":"2026-08-07T00:42:02.700113Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.700113Z"},"links":{"cited_paper":"/paper/2212.09803","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:f4b142a64ca4d3c6abe0408715bdb89b9f9043ceededc492d28732bab0be5a7b","observation_id":"87b1c8c5-13f9-4c96-aac4-392dacadbba9","resolution":{"observed_at":"2026-08-07T00:42:02.700113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-08-17T11:08:48.802438Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-07T00:42:02.816662Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.816662Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:9a093cd4ff024aafc6bffd9dfa0c066747b67a1aa116ae356ca7fafd75eb6888","observation_id":"2cbf349e-b34f-4d50-93ef-eeb2fdef00ce","resolution":{"observed_at":"2026-08-07T00:42:02.816662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14947","last_updated":"2023-10-31T17:27:07Z","snapshot_observed_at":"2026-08-19T09:15:38.566899Z","submitted_at":"2023-05-24T09:35:34Z","title":"How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench","version":2},"cited_work":{"arxiv_id":"2305.14947","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.14947","snapshot_observed_at":"2026-08-07T00:42:04.061794Z","title":"How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench","venue":"cs.CL","work_id":"f59063f1-582c-4e60-9b1f-41a70c411f94","year":2023},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:02.982272Z"},"links":{"cited_paper":"/paper/2305.14947","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:cddd30eb046b88232d11e3227136be192d126b4eda37e5f019775031c293df1b","observation_id":"fa346af3-6301-42b3-bcc5-58d20e21c54d","resolution":{"observed_at":"2026-08-07T00:42:04.171085Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04652","last_updated":"2025-01-21T10:12:05Z","snapshot_observed_at":"2026-08-17T20:16:19.173618Z","submitted_at":"2024-03-07T16:52:49Z","title":"Yi: Open Foundation Models by 01.AI","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04652","snapshot_observed_at":"2026-08-07T00:42:03.138335Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:03.138335Z"},"links":{"cited_paper":"/paper/2403.04652","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:8c8b99086d0dd3e265c2388095bb56de3bf3a931744da5d3af578e8642e710a4","observation_id":"d48bbfed-e2c7-409b-831b-714a10103cb7","resolution":{"observed_at":"2026-08-07T00:42:03.138335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.07830","last_updated":"2019-05-19T23:57:23Z","snapshot_observed_at":"2026-08-15T09:37:44.321271Z","submitted_at":"2019-05-19T23:57:23Z","title":"HellaSwag: Can a Machine Really Finish Your Sentence?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.07830","snapshot_observed_at":"2026-08-07T00:42:03.322283Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:03.322283Z"},"links":{"cited_paper":"/paper/1905.07830","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:5f7fc12ad9a280db80abba5d0318ee6df7edee26d2f27be8b0ca36a31bbc4d93","observation_id":"26e27fe6-c587-4a97-b013-deb39986be93","resolution":{"observed_at":"2026-08-07T00:42:03.322283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01300","last_updated":"2024-10-02T18:41:02Z","snapshot_observed_at":"2026-08-20T03:51:27.598959Z","submitted_at":"2024-07-01T13:56:42Z","title":"Collaborative Performance Prediction for Large Language Models","version":2},"cited_work":{"arxiv_id":"2407.01300","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.01300","snapshot_observed_at":"2026-08-07T00:42:03.854532Z","title":"Collaborative Performance Prediction for Large Language Models","venue":"cs.CL","work_id":"24f08813-b4f2-462f-8f35-f76b4a33114b","year":2024},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:03.480319Z"},"links":{"cited_paper":"/paper/2407.01300","citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:73634ad67ee8e59177c953956881bb5a5e6bd39c0503cdaeab13b319973a8c05","observation_id":"011f2f21-f0f6-417f-a427-dd566d70cc5f","resolution":{"observed_at":"2026-08-07T00:42:03.902498Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-07T00:42:03.627047Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:03.627047Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:422db37902d5d170e9c0a3b1ab1a12844cd70b477a9efddeb3981c679589e5da","observation_id":"ee42030b-3be9-4092-840a-3d8c134a8ab8","resolution":{"observed_at":"2026-08-07T00:42:03.627047Z","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":"2026-08-07T00:42:03.731235Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:03.731235Z"},"links":{"citing_paper":"/paper/2506.13216"},"observation_digest":"sha256:596cdd86e94d7ffad34452b3df51588b84b71b7bcbcb720192847c7327ea0635","observation_id":"6bcaf595-291c-452b-921b-a8ce658579dd","resolution":{"observed_at":"2026-08-07T00:42:03.731235Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.13216","last_updated":"2025-06-16T08:16:03Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T23:06:14.528660Z","submitted_at":"2025-06-16T08:16:03Z","title":"Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":40},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.13216."}