{"as_of":"2026-08-14T02:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:801f95ae878db7a40c3943b50b99e715b86a1ad98ce5750a8e258029849b8ec8","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:33:38.451145Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-19T16:47:09.487360Z","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":"2026-05-19T16:47:39.962921Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"cited_work":{"arxiv_id":"2501.07886","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.07886","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Iterative label refinement matters more than preference optimization under weak supervision","venue":null,"work_id":"12bd644a-8578-4b18-8fa9-494b3d751a62","year":2025},"citing_paper":{"arxiv_id":"2604.28111","last_updated":"2026-05-15T09:56:57Z","snapshot_observed_at":"2026-07-06T23:13:29.310140Z","submitted_at":"2026-04-30T16:59:07Z","title":"GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-07T06:23:39.902215Z"},"links":{"cited_paper":"/paper/2501.07886","citing_paper":"/paper/2604.28111"},"observation_digest":"sha256:4ff7a776c5910b412deec8e623915c162d3cc38082a46df30583d8a7ca10bc3f","observation_id":"5996dd99-2fc2-431b-8066-11056495acab","resolution":{"observed_at":"2026-05-12T10:21:30.635983Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"cited_work":{"arxiv_id":"2501.07886","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.07886","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Iterative label refinement matters more than preference optimization under weak supervision","venue":null,"work_id":"12bd644a-8578-4b18-8fa9-494b3d751a62","year":2025},"citing_paper":{"arxiv_id":"2604.28111","last_updated":"2026-05-15T09:56:57Z","snapshot_observed_at":"2026-07-06T23:13:29.310140Z","submitted_at":"2026-04-30T16:59:07Z","title":"GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-19T16:47:09.487360Z"},"links":{"cited_paper":"/paper/2501.07886","citing_paper":"/paper/2604.28111"},"observation_digest":"sha256:9c0fa2e8a039b608a047b37aea5d8cffeda5750bb9b6562c31591d89e21a0192","observation_id":"be7e3430-ca8d-46f9-b96d-7ab32ca0d3bd","resolution":{"observed_at":"2026-05-19T16:47:39.964563Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.07886/citation-record","integrity":"/paper/2501.07886/integrity","json":"/paper/2501.07886/citation-record.json","paper":"/paper/2501.07886"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:33:39.041571Z","title":null,"venue":null,"work_id":"c27e7583-47dd-469e-b659-b4faad939b9f","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.238026Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:693f83f0954e221981ebbe3395c67dcf517675900ca7c919810d14c2af7d6a94","observation_id":"2aff00f7-80e6-4134-ae0c-e1b218385610","resolution":{"observed_at":"2026-08-10T20:33:39.055588Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-10T20:33:38.932230Z","title":"Yesterday, she just did 50 minutes of babysitting","venue":null,"work_id":"92845ba5-25a1-43a1-89f9-cd58b6020bef","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.278264Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:cfa82b9853bc6dd55c9b4c95332f57e1f68e468610e025240320a49e47381b15","observation_id":"967ca301-c374-4e97-9d2c-294b2d3342ab","resolution":{"observed_at":"2026-08-10T20:33:38.978388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-10T20:33:38.892941Z","title":"Also, please give me a list of steps to cook it","venue":null,"work_id":"8ba4aa4d-4fe8-4cc3-b670-a90c4c3819c8","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.350705Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:914509ffcc72a3487cd478f3c34e398e04b2720530b3083a93ed60288c1022eb","observation_id":"5abf9c97-83a0-4264-95c1-a853b43df0bd","resolution":{"observed_at":"2026-08-10T20:33:38.905851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03277","last_updated":"2023-04-06T17:58:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-06T17:58:09Z","title":"Instruction Tuning with GPT-4","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03277","snapshot_observed_at":"2026-08-10T20:33:38.207048Z","title":"A note on dpo with noisy preferences & relationship to ipo, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.207048Z"},"links":{"cited_paper":"/paper/2304.03277","citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:16324c86e71e052ba1720af1c60456f56accffbb8c6c69d09e880efe8a1ef71a","observation_id":"f8d10f3b-405c-44b9-b969-a988077009ae","resolution":{"observed_at":"2026-08-10T20:33:38.207048Z","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":"2026-08-10T20:33:39.095338Z","title":"ophthalmologist","venue":null,"work_id":"cc180cc6-4270-479d-a9ad-af3185495cde","year":2024},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.228167Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:08fc1c604ad3f47a7a653ed198a7f599f8608da62fb86e3530960d4016272626","observation_id":"a289eb39-693d-4e3f-9c63-76a4b5cd9e06","resolution":{"observed_at":"2026-08-10T20:33:39.107540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-10T20:33:38.817225Z","title":"Response B: Water that has its salt removed before it can be used as drinking water is most likely to have come from a lake","venue":null,"work_id":"89d3d88f-9c5a-4133-8529-72b3008c257d","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.417458Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:1d963aebfb436d5c4d2d7e94005881c4f66ec5116671756eca02c1e81e48dde7","observation_id":"59b17994-dc59-4458-a85f-b169e9303b66","resolution":{"observed_at":"2026-08-10T20:33:38.844527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-10T20:33:38.753271Z","title":"Input: How can I compute the area of a circle with radius 5? Response A: The area of it is 25π","venue":null,"work_id":"debd4443-2e5e-4d1d-b371-2711d64b0420","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.443537Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:330f7310db57accce93aaa3aa5dc273ea051b73dc6af0bd2cfde039c0e0a8495","observation_id":"e3e5b731-0063-4c43-a89c-83aa56f6f9fa","resolution":{"observed_at":"2026-08-10T20:33:38.762971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-10T20:33:38.673784Z","title":null,"venue":null,"work_id":"d1df3894-507d-4676-9a9a-62facb78eecc","year":null},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.451145Z"},"links":{"citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:e1f15e6aec73e3c969060fd7f8594097b418b6294ba5ef6ffb9d5616a4abd889","observation_id":"ffc57454-ac17-46b2-ab88-e6d36aef27a3","resolution":{"observed_at":"2026-08-10T20:33:38.735467Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.13692","last_updated":"2024-08-01T17:18:54Z","snapshot_observed_at":"2026-08-12T23:19:17.040595Z","submitted_at":"2024-07-18T16:58:18Z","title":"Prover-Verifier Games improve legibility of LLM outputs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.13692","snapshot_observed_at":"2026-08-10T20:33:38.188792Z","title":"Prover-verifier games improve legibility of llm outputs","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.188792Z"},"links":{"cited_paper":"/paper/2407.13692","citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:77be5bc8820bfd05a01acca6091b9370e21322092b3a228d476029b4acd3289d","observation_id":"903a90db-54c4-4435-a4f7-d99fb61b5ab4","resolution":{"observed_at":"2026-08-10T20:33:38.188792Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-10T20:33:38.214096Z","title":"Sorry, I cannot help with that","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.214096Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:7c40e7167e3cb3d6e65cdec797665fe5b6c169139e59d73e344c705e15f86019","observation_id":"bfe683c6-c116-4a2e-ad9f-5802d987aae0","resolution":{"observed_at":"2026-08-10T20:33:38.214096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00215","last_updated":"2024-06-28T19:53:17Z","snapshot_observed_at":"2026-08-12T23:32:25.133777Z","submitted_at":"2024-06-28T19:53:17Z","title":"LLM Critics Help Catch LLM Bugs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00215","snapshot_observed_at":"2026-08-10T20:33:38.200106Z","title":"Llm critics help catch llm bugs","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.200106Z"},"links":{"cited_paper":"/paper/2407.00215","citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:d01f3992e5c772ae67df4be34c6406284fc8ab5a5475fa2786fe83ee636e5dad","observation_id":"103d1241-3dc4-4e3c-89d8-bec9e63a76df","resolution":{"observed_at":"2026-08-10T20:33:38.200106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.19316","last_updated":"2025-03-03T08:22:25Z","snapshot_observed_at":"2026-08-12T23:54:55.785946Z","submitted_at":"2024-05-29T17:39:48Z","title":"Robust Preference Optimization through Reward Model Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.19316","snapshot_observed_at":"2026-08-10T20:33:38.117776Z","title":"Robust preference optimization through reward model distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:38.117776Z"},"links":{"cited_paper":"/paper/2405.19316","citing_paper":"/paper/2501.07886"},"observation_digest":"sha256:253753ed7f58f1ca1b5bb0b7cc0b3cee6db8ee1f9d25eee9e1ceef0796e2ae86","observation_id":"c33e8a6f-fb43-49f3-87bb-1f9cc38cc0a5","resolution":{"observed_at":"2026-08-10T20:33:38.117776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.07886","last_updated":"2025-01-14T06:54:17Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T20:28:41.525071Z","submitted_at":"2025-01-14T06:54:17Z","title":"Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":5},"total_outbound_references":12},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2501.07886."}