{"as_of":"2026-08-12T09:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:91970d495d36263a9d637b0cbe48bff6b5c4c976dce999303ecf6f1fa944117c","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T12:31:29.883504Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2607.24522/citation-record","integrity":"/paper/2607.24522/integrity","json":"/paper/2607.24522/citation-record.json","paper":"/paper/2607.24522"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-31T12:31:27.911132Z","title":"On-policy distillation of language models: Learning from self- generated mistakes","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:27.911132Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:9ba76727a60792ce2c0ee2ad40ece82cf7822a20860bff8f904616126d78095b","observation_id":"9681bb56-9043-4674-89f2-cb3c666cb23a","resolution":{"observed_at":"2026-07-31T12:31:27.911132Z","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":"2026-07-31T12:31:29.883504Z","title":"Models marked with‡in Table 3 are evaluated at1024×1024","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.883504Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:9517f85ea064a0b1473f7f8a3df0375286345514763afb073f1d06c937207a54","observation_id":"e068e508-122f-45cd-8f33-e878fcb6b94c","resolution":{"observed_at":"2026-07-31T12:31:29.883504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07507","last_updated":"2025-06-03T00:03:07Z","snapshot_observed_at":"2026-08-08T12:26:21.521950Z","submitted_at":"2024-06-11T17:41:26Z","title":"Flow map matching with stochastic interpolants: A mathematical framework for consistency models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07507","snapshot_observed_at":"2026-07-31T12:31:28.095463Z","title":"Flow map matching with stochastic interpolants: A mathematical framework for consistency models.arXiv preprint arXiv:2406.07507,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.095463Z"},"links":{"cited_paper":"/paper/2406.07507","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:a1cd60fb7d046d1efcf1a2ba6baa30fe3cfc022fcf1bab1de2b71b5ebd4d5e78","observation_id":"7f15b8b4-c9df-44f7-92e7-22c38a5a840e","resolution":{"observed_at":"2026-07-31T12:31:28.095463Z","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":"2026-07-31T12:31:28.169785Z","title":"Directly fine-tuning diffusion models on differentiable rewards","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.169785Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:d3ba19e555563c79f239a408ffa9ffd5867f98494485ae417e2deaf66a760d9f","observation_id":"2ceef94c-d428-4e56-b542-abae7190ea46","resolution":{"observed_at":"2026-07-31T12:31:28.169785Z","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":"2026-07-31T12:31:28.472230Z","title":"Minillm: Knowledge distillation of large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.472230Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:0be8a550f977f658d33b32e4d6fcf1510b25c6250da139d32cfa1cde16c0b0d8","observation_id":"87d43d78-4437-465d-931d-9112d1fbb3e8","resolution":{"observed_at":"2026-07-31T12:31:28.472230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.04324","last_updated":"2025-10-15T06:35:29Z","snapshot_observed_at":"2026-07-06T22:08:40.965707Z","submitted_at":"2025-08-06T11:10:39Z","title":"TempFlow-GRPO: When Timing Matters for GRPO in Flow Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.04324","snapshot_observed_at":"2026-07-31T12:31:28.502759Z","title":"Tempflow-grpo: When timing matters for grpo in flow models.arXiv preprint arXiv:2508.04324,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.502759Z"},"links":{"cited_paper":"/paper/2508.04324","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:a426681272810fb6de029ac94e8207743c778e35e78cb88c8c9a17ca8d61f9c8","observation_id":"13f1879a-f268-4a39-8906-70d90bbfc81b","resolution":{"observed_at":"2026-07-31T12:31:28.502759Z","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":"2026-07-31T12:31:28.628563Z","title":"Consistency trajectory models: Learning proba- bility flow ode trajectory of diffusion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.628563Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:b9a4636efd476fb349d78e6c06b0ec27e7c8495362b73d43c4d99eadf95d0e9c","observation_id":"eac3fe3d-011d-4420-a49b-ea4a02aebe90","resolution":{"observed_at":"2026-07-31T12:31:28.628563Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.13117","last_updated":"2024-11-07T11:45:10Z","snapshot_observed_at":"2026-08-11T18:48:11.907535Z","submitted_at":"2024-03-19T19:44:54Z","title":"Optimal Flow Matching: Learning Straight Trajectories in Just One Step","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.13117","snapshot_observed_at":"2026-07-31T12:31:28.715364Z","title":"Optimal flow matching: Learning straight trajectories in just one step.arXiv preprint arXiv:2403.13117,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.715364Z"},"links":{"cited_paper":"/paper/2403.13117","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:e140f887980227be50d78a3ba684775c1fb4c999045288cc6119169ea347f18f","observation_id":"007b9146-9c90-47c0-808c-c5b3ed86f7c2","resolution":{"observed_at":"2026-07-31T12:31:28.715364Z","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":"2026-07-31T12:31:28.779432Z","title":"Kat-coder-v2 technical report.arXiv preprint arXiv:2603.27703, 2026a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.779432Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:5da97d7c6b28a4cd81522d995b6232cc7985677264f7ff8a52b15e752dd19294","observation_id":"352656d5-7222-4e47-9d27-0b220cb3f9ae","resolution":{"observed_at":"2026-07-31T12:31:28.779432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.30406","last_updated":"2026-06-29T14:51:28Z","snapshot_observed_at":"2026-08-10T09:37:40.339025Z","submitted_at":"2026-06-29T14:51:28Z","title":"MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.30406","snapshot_observed_at":"2026-07-31T12:31:28.951991Z","title":"https://thinkingmachines.ai/blog/on-policy-distillation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.951991Z"},"links":{"cited_paper":"/paper/2606.30406","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:5827204ea7eca8becd15f33a32713a9b27338e2f95502acd9ff7cfe44bda6872","observation_id":"750f1357-effc-4db1-a007-0717957e24f5","resolution":{"observed_at":"2026-07-31T12:31:28.951991Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.00512","last_updated":"2022-06-07T09:17:35Z","snapshot_observed_at":"2026-08-12T01:14:44.484432Z","submitted_at":"2022-02-01T16:07:25Z","title":"Progressive Distillation for Fast Sampling of Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.00512","snapshot_observed_at":"2026-07-31T12:31:29.022066Z","title":"Progressive distillation for fast sampling of diffusion models.arXiv preprint arXiv:2202.00512,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.022066Z"},"links":{"cited_paper":"/paper/2202.00512","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:b7a4d450ee5a2c20bf7ad05897aca42ce88f00c1c89a9ec1ec60cba648afd49d","observation_id":"079af189-e604-4b18-ab32-2d13a3fd097c","resolution":{"observed_at":"2026-07-31T12:31:29.022066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.00482","last_updated":"2024-03-11T14:27:48Z","snapshot_observed_at":"2026-07-06T14:47:04.817434Z","submitted_at":"2023-02-01T14:47:17Z","title":"Improving and generalizing flow-based generative models with minibatch optimal transport","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.00482","snapshot_observed_at":"2026-07-31T12:31:29.105915Z","title":"Improving and generalizing flow-based generative models with minibatch optimal transport.arXiv preprint arXiv:2302.00482,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.105915Z"},"links":{"cited_paper":"/paper/2302.00482","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:bb1e2661966531366094dfb9fe0255c7394f8da2cb59899c85441955d251485a","observation_id":"34818620-2dbe-49de-af34-4eb7af98bfdc","resolution":{"observed_at":"2026-07-31T12:31:29.105915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02780","last_updated":"2026-01-08T05:52:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-01-06T07:31:47Z","title":"MiMo-V2-Flash Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.02780","snapshot_observed_at":"2026-07-31T12:31:29.194152Z","title":"Mimo-v2-flash technical report.arXiv preprint arXiv:2601.02780,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.194152Z"},"links":{"cited_paper":"/paper/2601.02780","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:d258745f1bc0a39e2a94de4b4b9b9e301f98b3349949280a9b21091bf1452f4d","observation_id":"c7acfeba-62ed-402e-9bdf-76db101c311d","resolution":{"observed_at":"2026-07-31T12:31:29.194152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.07818","last_updated":"2025-08-28T17:19:45Z","snapshot_observed_at":"2026-08-10T06:20:33.458844Z","submitted_at":"2025-05-12T17:59:34Z","title":"DanceGRPO: Unleashing GRPO on Visual Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.07818","snapshot_observed_at":"2026-07-31T12:31:29.285382Z","title":"Dancegrpo: Unleashing grpo on visual generation.arXiv preprint arXiv:2505.07818,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.285382Z"},"links":{"cited_paper":"/paper/2505.07818","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:345c51d259ea4715d3be62e0191331d9a7deebe4db48e1bc7403a306b0b04e31","observation_id":"331132f6-4adc-4338-9736-301193fb27b8","resolution":{"observed_at":"2026-07-31T12:31:29.285382Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-07-31T12:31:29.357770Z","title":"Qwen3 technical report.arXiv preprint arXiv:2505.09388,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.357770Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:480c37686e77d71342c7918692514077804990f2bda5c11fa80ab2ba8c07f29f","observation_id":"38234697-fc1f-41d8-9a7a-1a9570bec849","resolution":{"observed_at":"2026-07-31T12:31:29.357770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.12125","last_updated":"2026-02-26T13:26:22Z","snapshot_observed_at":"2026-07-31T18:08:52.441829Z","submitted_at":"2026-02-12T16:14:29Z","title":"Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.12125","snapshot_observed_at":"2026-07-31T12:31:29.453327Z","title":"Learning beyond teacher: Generalized on-policy distillation with reward extrapolation.arXiv preprint arXiv:2602.12125,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.453327Z"},"links":{"cited_paper":"/paper/2602.12125","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:b139053143cbfe9f88d6320db0f2544e224a080194b28e1bd478e43aea0b24f7","observation_id":"7e4d5940-89fd-4032-b417-8e7a17642eec","resolution":{"observed_at":"2026-07-31T12:31:29.453327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.15763","last_updated":"2026-02-24T10:44:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-17T17:50:56Z","title":"GLM-5: from Vibe Coding to Agentic Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.15763","snapshot_observed_at":"2026-07-31T12:31:29.565270Z","title":"Improved distribution matching distillation for fast image synthesis.Ad- vances in neural information processing systems, 37:47455–47487, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.565270Z"},"links":{"cited_paper":"/paper/2602.15763","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:48094d77adc6fb5d19c2f29bbf528961958eaac997a1ba1a1e232402eac53c8a","observation_id":"29c9830f-e9ae-4219-b537-54e9d13d878d","resolution":{"observed_at":"2026-07-31T12:31:29.565270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.16117","last_updated":"2026-02-16T17:14:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-19T16:09:33Z","title":"DiffusionNFT: Online Diffusion Reinforcement with Forward Process","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.16117","snapshot_observed_at":"2026-07-31T12:31:29.711276Z","title":"Diffusionnft: Online diffusion reinforcement with forward process.arXiv preprint arXiv:2509.16117,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.711276Z"},"links":{"cited_paper":"/paper/2509.16117","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:0ec1e2d0f71103538bb273fc3b23f3cb60f7d5fd729ab48885d6f86dfe8e03ae","observation_id":"f0010592-1585-4e5e-873e-e5296b7eb444","resolution":{"observed_at":"2026-07-31T12:31:29.711276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.27377","last_updated":"2026-07-07T04:28:57Z","snapshot_observed_at":"2026-08-10T04:12:12.809965Z","submitted_at":"2026-06-25T17:59:58Z","title":"DanceOPD: On-Policy Generative Field Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.27377","snapshot_observed_at":"2026-07-31T12:31:29.793903Z","title":"Danceopd: On-policy generative field distillation.arXiv preprint arXiv:2606.27377,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:29.793903Z"},"links":{"cited_paper":"/paper/2606.27377","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:5f1da2d3342f51240065b3f2d119c9821adc3b838e47cb6f2385a6919fd1779e","observation_id":"1749f991-f867-48de-891f-91d1aec0c2bb","resolution":{"observed_at":"2026-07-31T12:31:29.793903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.03003","last_updated":"2022-09-07T08:59:55Z","snapshot_observed_at":"2026-07-06T13:49:40.974495Z","submitted_at":"2022-09-07T08:59:55Z","title":"Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.03003","snapshot_observed_at":"2026-07-31T12:31:28.843418Z","title":"Flow-grpo: Training flow matching models via online rl.Ad- vances in neural information processing systems, 38:40783–40818, 2026a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.843418Z"},"links":{"cited_paper":"/paper/2209.03003","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:5d769c7f4f9c8cca257673586ab6cc32417f948329308d51fd2c3f9ea8ae2675","observation_id":"a0201845-5324-4396-8890-54aa7a629be5","resolution":{"observed_at":"2026-07-31T12:31:28.843418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.08063","last_updated":"2026-05-24T05:25:48Z","snapshot_observed_at":"2026-08-11T06:20:19.198189Z","submitted_at":"2026-05-08T17:50:15Z","title":"Flow-OPD: On-Policy Distillation for Flow Matching Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.08063","snapshot_observed_at":"2026-07-31T12:31:28.249661Z","title":"Flow-opd: On-policy distillation for flow matching models.arXiv preprint arXiv:2605.08063,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.249661Z"},"links":{"cited_paper":"/paper/2605.08063","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:82a573ef05127ad51cdea48f8c9ccd1474d58aec47a1fa0d2c3223a0c000d9d1","observation_id":"5190c60f-9532-4e49-ba57-d44ea1828e54","resolution":{"observed_at":"2026-07-31T12:31:28.249661Z","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":"2026-07-31T12:31:28.025170Z","title":"Training diffusion models with reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.025170Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:3d1b5e161ae36cfead92b037992f209736331da65aabcb3f3f9a91dcc9d05bab","observation_id":"168a3b97-a8f3-4638-b83b-378d90a03cff","resolution":{"observed_at":"2026-07-31T12:31:28.025170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.03677","last_updated":"2026-07-06T06:34:16Z","snapshot_observed_at":"2026-08-11T09:47:09.096143Z","submitted_at":"2026-05-05T12:15:21Z","title":"Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.03677","snapshot_observed_at":"2026-07-31T12:31:28.555580Z","title":"Uni-opd: Unifying on-policy distillation with a dual-perspective recipe.arXiv preprint arXiv:2605.03677,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.555580Z"},"links":{"cited_paper":"/paper/2605.03677","citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:b12145800c0b81476509b5e0bc8777354711f55701169bd6d65cebba8aaf25fd","observation_id":"f533d8e1-0931-445e-bcf2-055fafe5559a","resolution":{"observed_at":"2026-07-31T12:31:28.555580Z","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":"2026-07-31T12:31:28.397225Z","title":"One step diffusion via shortcut models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-07-31T12:31:28.397225Z"},"links":{"citing_paper":"/paper/2607.24522"},"observation_digest":"sha256:62feae64185c6294f50169b02669e9ac157f0b70cf9ef6ed277c6586a89e3d3e","observation_id":"92d54ba2-d871-4191-8ce7-7a2049acea7b","resolution":{"observed_at":"2026-07-31T12:31:28.397225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.24522","last_updated":"2026-07-27T15:03:22Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T15:46:02.023742Z","submitted_at":"2026-07-27T15:03:22Z","title":"FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":24,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":24},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.24522."}