{"as_of":"2026-08-08T00:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:67e1fc35452df885368510ae254dfc22cb16d3cb439739dde8a2035bae54524a","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:54:17.301615Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08561","snapshot_observed_at":"2026-08-06T17:54:17.301615Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09662","last_updated":"2025-07-13T14:51:59Z","snapshot_observed_at":"2026-08-07T01:15:50.475193Z","submitted_at":"2025-07-13T14:51:59Z","title":"Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey","version":1},"reference_index":115,"source":"arxiv_source","source_observed_at":"2026-08-06T17:54:17.301615Z"},"links":{"cited_paper":"/paper/2409.08561","citing_paper":"/paper/2507.09662"},"observation_digest":"sha256:f59fa5ba47d2b5169c1f4660312932286a736fc0039cd3a360b08f06770416f1","observation_id":"6f4c3d11-b655-4b01-860c-774f9ae67b8b","resolution":{"observed_at":"2026-08-06T17:54:17.301615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08561","snapshot_observed_at":"2026-08-05T11:39:36.653341Z","title":"Can language models learn to skip steps? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02350","last_updated":"2025-09-02T14:16:02Z","snapshot_observed_at":"2026-08-07T15:04:01.909916Z","submitted_at":"2025-09-02T14:16:02Z","title":"Implicit Reasoning in Large Language Models: A Comprehensive Survey","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T11:39:36.653341Z"},"links":{"cited_paper":"/paper/2409.08561","citing_paper":"/paper/2509.02350"},"observation_digest":"sha256:03f092eff6cfa1c8b5dcd6bd85a30c028ed0c6a6a9696338663782b0dafedb09","observation_id":"499b6c8f-943c-4ef0-929a-00d683b5c6ff","resolution":{"observed_at":"2026-08-05T11:39:36.653341Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08561","snapshot_observed_at":"2026-07-13T14:03:01.974171Z","title":"Expediting and elevating large language model reasoning via hidden chain-of-thought decoding.CoRR, abs/2409.08561, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.02029","last_updated":"2026-06-05T06:21:20Z","snapshot_observed_at":"2026-07-30T23:04:23.206455Z","submitted_at":"2026-04-02T13:36:37Z","title":"The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook","version":2},"reference_index":128,"source":"pdf_text","source_observed_at":"2026-07-13T14:03:01.974171Z"},"links":{"cited_paper":"/paper/2409.08561","citing_paper":"/paper/2604.02029"},"observation_digest":"sha256:783396e607987ee73544cd0c1e7c8c006986ffa7bb0730d7bd77b7828dfe6042","observation_id":"c487a949-6036-4f8d-8a53-c11676e40bda","resolution":{"observed_at":"2026-07-13T14:03:01.974171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding","version":1},"cited_work":{"arxiv_id":"2409.08561","doi":"10.48550/arxiv.2409.08561","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.08561","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Expediting and","venue":"arXiv (Cornell University)","work_id":"9e63578d-3fc4-4239-a56a-e6c6684c8f82","year":null},"citing_paper":{"arxiv_id":"2604.21027","last_updated":"2026-08-02T16:15:42Z","snapshot_observed_at":"2026-08-06T23:24:26.820832Z","submitted_at":"2026-04-22T19:18:36Z","title":"HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-05-09T23:51:47.724033Z"},"links":{"cited_paper":"/paper/2409.08561","citing_paper":"/paper/2604.21027"},"observation_digest":"sha256:83312f23d3ade623e0567f2d4237a442ae6469b3a9f1d54f943b7394a2457145","observation_id":"5b4d2705-54c5-4cf4-8e38-240efc847e6a","resolution":{"observed_at":"2026-05-09T23:54:45.686773Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-01T13:38:11.600193+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T13:38:11.600193+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08561","snapshot_observed_at":"2026-08-01T07:51:12.714284Z","title":"arXiv preprint arXiv:2409.08561 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21333","last_updated":"2026-07-23T14:00:09Z","snapshot_observed_at":"2026-08-05T03:11:52.952262Z","submitted_at":"2026-07-23T14:00:09Z","title":"SHIFT: Self-reconstruction Harnesses Implicit Fine-grained Thinking for Retrieval","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T07:51:12.714284Z"},"links":{"cited_paper":"/paper/2409.08561","citing_paper":"/paper/2607.21333"},"observation_digest":"sha256:966189c89fa1768f41a2b87ca052359bdd241ddd0e9478028f69bf34794f34d0","observation_id":"fe6825dc-4286-44b7-985e-8a9196faf7a6","resolution":{"observed_at":"2026-08-01T07:51:12.714284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2409.08561/citation-record","integrity":"/paper/2409.08561/integrity","json":"/paper/2409.08561/citation-record.json","paper":"/paper/2409.08561"},"outbound":[],"paper":{"arxiv_id":"2409.08561","last_updated":"2024-09-13T06:29:20Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T09:20:42.774778Z","submitted_at":"2024-09-13T06:29:20Z","title":"Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.08561."}