{"as_of":"2026-08-09T01:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54ee69325ff1178e3d76dd784198a2951e1f8812e237dbfd4142bf031bc355af","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:42:27.388786Z","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":"2026-05-21T14:54:13.227676Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-08-07T14:42:27.388786Z","title":"Litesearch: Efficacious tree search for llm.arXiv preprint arXiv:2407.00320, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18065","last_updated":"2025-05-23T16:12:12Z","snapshot_observed_at":"2026-08-08T14:50:33.225594Z","submitted_at":"2025-05-23T16:12:12Z","title":"Reward Model Generalization for Compute-Aware Test-Time Reasoning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T14:42:27.388786Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2505.18065"},"observation_digest":"sha256:344589102752d87bbf013f6ceda6e8de96ef9f8821fe8e22defb7bb865f4c972","observation_id":"ff489b9b-8686-4b99-929b-ebd174b217a5","resolution":{"observed_at":"2026-08-07T14:42:27.388786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-08-07T14:21:22.655375Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19250","last_updated":"2025-05-25T17:58:50Z","snapshot_observed_at":"2026-08-08T11:21:53.639135Z","submitted_at":"2025-05-25T17:58:50Z","title":"PATS: Process-Level Adaptive Thinking Mode Switching","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T14:21:22.655375Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2505.19250"},"observation_digest":"sha256:a6722571182d9e29e88fac3067aa23f098f67ee77ddca256882ed35a9995dd4f","observation_id":"fb7f4d06-42a7-4e5d-b9cb-b47323f6b1cf","resolution":{"observed_at":"2026-08-07T14:21:22.655375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-08-06T23:57:21.815062Z","title":"Litesearch: Efficacious tree search for llm.arXiv preprint arXiv:2407.00320, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15649","last_updated":"2025-06-18T17:23:36Z","snapshot_observed_at":"2026-08-07T09:16:49.443338Z","submitted_at":"2025-06-18T17:23:36Z","title":"Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T23:57:21.815062Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2506.15649"},"observation_digest":"sha256:2f31a7d998daba70bb99d2d1d810cf79fd7f3bb78f10bbd9c7e23b0184c0f940","observation_id":"c3f05ff3-ff21-47a7-97b6-7bcc71065d9e","resolution":{"observed_at":"2026-08-06T23:57:21.815062Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-08-04T18:53:02.763705Z","title":"Litesearch: Efficacious tree search for llm.arXiv preprint arXiv:2407.00320, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.09675","last_updated":"2025-09-11T17:59:17Z","snapshot_observed_at":"2026-08-07T12:25:43.109797Z","submitted_at":"2025-09-11T17:59:17Z","title":"CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T18:53:02.763705Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2509.09675"},"observation_digest":"sha256:772252e142de1618a8cca85479d2d0e1fefe5b8b227a47d5a991d28d744056c2","observation_id":"f22aacd1-a65f-4627-9d38-08d962735cec","resolution":{"observed_at":"2026-08-04T18:53:02.763705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-08-04T12:52:27.708575Z","title":"Litesearch: Efficacious tree search for llm","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.01833","last_updated":"2026-05-25T18:23:42Z","snapshot_observed_at":"2026-08-04T12:52:24.589866Z","submitted_at":"2025-10-02T09:28:13Z","title":"Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-04T12:52:27.708575Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2510.01833"},"observation_digest":"sha256:1ba9527cc9ceab3cf6762e420a8d3cfc425671882a02a494f8282f1da2456e22","observation_id":"3f37df55-e1ca-4012-9565-c7425f665971","resolution":{"observed_at":"2026-08-04T12:52:27.708575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM","version":1},"cited_work":{"arxiv_id":"2407.00320","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.00320","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"LiteSearch:EfficacioustreesearchforLLM","venue":null,"work_id":"3e8a7d67-884e-4cb1-af41-cd0c8714cb5e","year":2024},"citing_paper":{"arxiv_id":"2602.03433","last_updated":"2026-02-03T11:56:08Z","snapshot_observed_at":"2026-08-08T17:54:42.368266Z","submitted_at":"2026-02-03T11:56:08Z","title":"When control meets large language models: From words to dynamics","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-05-21T14:52:44.632671Z"},"links":{"cited_paper":"/paper/2407.00320","citing_paper":"/paper/2602.03433"},"observation_digest":"sha256:1c2bdd593cea970af70b949429efc3927b29ebf00cbae705a381fad39bfd923b","observation_id":"c5c3a4e6-8ddc-4cca-a046-08d54115b719","resolution":{"observed_at":"2026-05-21T14:54:13.229508Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.00320/citation-record","integrity":"/paper/2407.00320/integrity","json":"/paper/2407.00320/citation-record.json","paper":"/paper/2407.00320"},"outbound":[],"paper":{"arxiv_id":"2407.00320","last_updated":"2024-06-29T05:14:04Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T10:09:18.664387Z","submitted_at":"2024-06-29T05:14:04Z","title":"LiteSearch: Efficacious Tree Search for LLM"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.00320."}