{"as_of":"2026-08-04T07:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7da904fdaa2fd2499306b7c8dd934ef2e6e64907b683dcdc34fd0afa3f673338","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T06:54:13.660206Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-08T13:54:58.614474Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2406.18495","last_updated":"2024-12-09T20:21:56Z","snapshot_observed_at":"2026-08-03T14:57:10.257731Z","submitted_at":"2024-06-26T16:58:20Z","title":"WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-17T16:25:14.744887Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2406.18495"},"observation_digest":"sha256:2e4b570a43798492e0db6dbbbdd19677480f4f603ca0c97c607f012b8e7e1143","observation_id":"c95dd37a-65d2-4051-8125-61a75faa3f98","resolution":{"observed_at":"2026-05-17T16:25:14.910778Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2505.22073","last_updated":"2025-06-02T19:08:46Z","snapshot_observed_at":"2026-07-06T21:31:59.333003Z","submitted_at":"2025-05-28T07:54:06Z","title":"A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-19T14:11:50.109906Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2505.22073"},"observation_digest":"sha256:fa3cf1a0698a2b6b7c5c06d6532847b9d28abe67c5837ba62adbdfb5a8bd6eae","observation_id":"b186ba0b-4eae-46e9-bf8c-302d587c38b0","resolution":{"observed_at":"2026-05-19T14:12:22.155301Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-08-04T06:54:13.660206Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.00382","last_updated":"2026-08-03T16:22:30Z","snapshot_observed_at":"2026-08-04T06:54:04.816319Z","submitted_at":"2025-11-01T03:29:56Z","title":"Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-04T06:54:13.660206Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2511.00382"},"observation_digest":"sha256:adcedea29670ae90934a6e019ddf6161fe9ae7fad6a42739476f5e818dc78cc7","observation_id":"6239235d-c0fe-4213-89bf-31da285061e5","resolution":{"observed_at":"2026-08-04T06:54:13.660206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2604.16542","last_updated":"2026-04-17T01:55:37Z","snapshot_observed_at":"2026-08-01T22:59:54.227625Z","submitted_at":"2026-04-17T01:55:37Z","title":"TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T09:07:57.713675Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2604.16542"},"observation_digest":"sha256:c9eb0c6bcb99cdc0ba1bb48559be85194292397a37fe9f8ced9e49c95f4bc5c7","observation_id":"aa810aa7-4335-41ff-af04-86dc9ad62cf3","resolution":{"observed_at":"2026-05-10T09:08:25.508279Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2604.18512","last_updated":"2026-04-20T17:06:20Z","snapshot_observed_at":"2026-07-06T23:05:21.974248Z","submitted_at":"2026-04-20T17:06:20Z","title":"S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models","version":1},"reference_index":126,"source":"arxiv_source","source_observed_at":"2026-05-10T05:38:01.208136Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2604.18512"},"observation_digest":"sha256:dd0fb70ad3370de4da535dce1933bc9c40df57d2ee48de78f7446d0a56d936b6","observation_id":"fa4fab60-4f78-4b84-93bc-d09fc322e449","resolution":{"observed_at":"2026-05-10T05:41:02.239274Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-13T18:51:10.298187Z","title":"Vidgen, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.00003","last_updated":"2026-03-25T15:36:15Z","snapshot_observed_at":"2026-07-13T18:51:10.077827Z","submitted_at":"2026-03-25T15:36:15Z","title":"Learning from Mistakes: Can LLM Self-Recover after Misalignment?","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-13T18:51:10.298187Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2606.00003"},"observation_digest":"sha256:6cad7f73b39a71a0be6e6efbf9988bf190eedc74bf10d6c681135cd52bd7e78b","observation_id":"00c58042-158f-4070-9cf8-bd4a1b5f5813","resolution":{"observed_at":"2026-07-13T18:51:10.298187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2606.28387","last_updated":"2026-06-23T02:20:36Z","snapshot_observed_at":"2026-08-02T20:33:53.738251Z","submitted_at":"2026-06-23T02:20:36Z","title":"Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-06-30T10:38:24.972419Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2606.28387"},"observation_digest":"sha256:ebe399d1f5af76e402f3ac7b6e31fe648a4379502e07c6f76d888015be66d591","observation_id":"5a39da39-9fbb-40c8-a675-d0c71f055776","resolution":{"observed_at":"2026-06-30T10:44:36.734735Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2607.01457","last_updated":"2026-07-01T20:22:18Z","snapshot_observed_at":"2026-07-07T00:06:59.129459Z","submitted_at":"2026-07-01T20:22:18Z","title":"Grounded Optimization: A Layered Engineering Framework for Reducing LLM Hallucination in Automated Personal Document Rewriting","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-03T21:05:26.764993Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2607.01457"},"observation_digest":"sha256:2e56ea653178693b626cf3152b6dbfb6cec4e04bf5e7936b34cc58b805329a75","observation_id":"67b2d984-ff10-4654-afc3-9c2894c5e3cb","resolution":{"observed_at":"2026-07-03T21:08:57.557430Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-12T14:28:50.627444Z","title":"5 of the ai safety benchmark from mlcommons , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.05407","last_updated":"2026-06-09T03:22:53Z","snapshot_observed_at":"2026-07-12T14:28:46.372811Z","submitted_at":"2026-06-09T03:22:53Z","title":"Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-07-12T14:28:50.627444Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2607.05407"},"observation_digest":"sha256:429046838b36635ccd5882b6901ede1a7ff3b495ad1360440acfe1d7e91eaa76","observation_id":"f13ce255-5e79-4098-beb1-51c6ae9b208c","resolution":{"observed_at":"2026-07-12T14:28:50.627444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":"2404.12241","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-07-08T13:54:58.614474Z","title":"Introducing v0.5 of the AI safety benchmark from MLCommons","venue":"cs.CL","work_id":"cf3860a3-9e35-40de-aba0-115059ef292a","year":2024},"citing_paper":{"arxiv_id":"2607.06196","last_updated":"2026-07-07T12:21:52Z","snapshot_observed_at":"2026-08-01T22:51:20.749089Z","submitted_at":"2026-07-07T12:21:52Z","title":"Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-07-08T13:50:54.083165Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2607.06196"},"observation_digest":"sha256:add012eb17d8de7c540c3d298f351a682fa04ca622b08365d8a89ca79a2a4bab","observation_id":"6e3228f3-0038-446b-a377-a6abc999f835","resolution":{"observed_at":"2026-07-08T13:54:58.615885Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2404.12241/citation-record","integrity":"/paper/2404.12241/integrity","json":"/paper/2404.12241/citation-record.json","paper":"/paper/2404.12241"},"outbound":[],"paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2404.12241."}