{"as_of":"2026-08-09T16:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:22e69ae8e8f778be78ba145060caad82ee4f91f8acc84943a2a653e20444753a","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":"2026-08-09T06:31:02.800959+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":"2026-08-08T19:15:54.834676Z","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":"2026-07-01T19:46:10.198763Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.00117","snapshot_observed_at":"2026-08-08T19:15:54.834676Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B , October 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.05475","last_updated":"2025-02-08T07:24:04Z","snapshot_observed_at":"2026-08-09T02:15:12.668653Z","submitted_at":"2025-02-08T07:24:04Z","title":"You Are What You Eat -- AI Alignment Requires Understanding How Data Shapes Structure and Generalisation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-08T19:15:54.834676Z"},"links":{"cited_paper":"/paper/2311.00117","citing_paper":"/paper/2502.05475"},"observation_digest":"sha256:c68a53135ec745cdeb6deba50d9d5eefddf854f6dc11587cf2e4b5f24e781e86","observation_id":"ec599caa-95bd-4082-b6ce-58083d407a17","resolution":{"observed_at":"2026-08-08T19:15:54.834676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.00117","snapshot_observed_at":"2026-08-07T12:11:19.162848Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05376","last_updated":"2025-06-09T05:48:22Z","snapshot_observed_at":"2026-08-07T12:39:09.825243Z","submitted_at":"2025-05-30T22:58:54Z","title":"A Red Teaming Roadmap Towards System-Level Safety","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:11:19.162848Z"},"links":{"cited_paper":"/paper/2311.00117","citing_paper":"/paper/2506.05376"},"observation_digest":"sha256:0b0af999036a980232a2d744cdfe19ff296ed8b386bf9b52397aa5e2d6880448","observation_id":"08b021ac-c43e-4300-af8a-d4d4eba68d5e","resolution":{"observed_at":"2026-08-07T12:11:19.162848Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B","version":3},"cited_work":{"arxiv_id":"2311.00117","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.00117","snapshot_observed_at":"2026-07-01T19:46:10.198763Z","title":"Badllama: cheaply removing safety fine-tuning from llama 2-chat 13b","venue":null,"work_id":"1c51b110-1eac-438f-b95d-59526cc76679","year":2023},"citing_paper":{"arxiv_id":"2506.06414","last_updated":"2026-04-20T20:58:30Z","snapshot_observed_at":"2026-08-03T02:03:44.971897Z","submitted_at":"2025-06-06T17:33:33Z","title":"Benchmarking Misuse Mitigation Against Covert Adversaries","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-19T10:29:05.104520Z"},"links":{"cited_paper":"/paper/2311.00117","citing_paper":"/paper/2506.06414"},"observation_digest":"sha256:d355a33d865834af598471f5f9908c9f2c7d706797ae546518778363e4810ad1","observation_id":"0f7840f5-8499-47b7-a8e1-564ffc0e4146","resolution":{"observed_at":"2026-05-19T10:32:14.732990Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B","version":3},"cited_work":{"arxiv_id":"2311.00117","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.00117","snapshot_observed_at":"2026-07-01T19:46:10.198763Z","title":"Badllama: cheaply removing safety fine-tuning from llama 2-chat 13b","venue":null,"work_id":"1c51b110-1eac-438f-b95d-59526cc76679","year":2023},"citing_paper":{"arxiv_id":"2605.16471","last_updated":"2026-05-15T13:53:02Z","snapshot_observed_at":"2026-07-06T23:27:38.955917Z","submitted_at":"2026-05-15T13:53:02Z","title":"From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-20T18:08:24.901025Z"},"links":{"cited_paper":"/paper/2311.00117","citing_paper":"/paper/2605.16471"},"observation_digest":"sha256:f5a8f04e3340db80a43c8854fdf5e3de69cd261c50263e2a94b7312b0efb7637","observation_id":"a536dd72-e86b-4e9c-a87f-cbd9cd0435ce","resolution":{"observed_at":"2026-05-20T18:08:50.520837Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B","version":3},"cited_work":{"arxiv_id":"2311.00117","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.00117","snapshot_observed_at":"2026-07-01T19:46:10.198763Z","title":"Badllama: cheaply removing safety fine-tuning from llama 2-chat 13b","venue":null,"work_id":"1c51b110-1eac-438f-b95d-59526cc76679","year":2023},"citing_paper":{"arxiv_id":"2606.00160","last_updated":"2026-05-29T09:04:27Z","snapshot_observed_at":"2026-08-02T07:42:30.512493Z","submitted_at":"2026-05-29T09:04:27Z","title":"DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T22:09:02.498712Z"},"links":{"cited_paper":"/paper/2311.00117","citing_paper":"/paper/2606.00160"},"observation_digest":"sha256:8f1f9824a6e443a11016d3644c9b146bccefb9f2c6466cfe8945547487ed87cb","observation_id":"1b5a062b-48dc-4d4a-a85b-49e3b7bf8612","resolution":{"observed_at":"2026-07-01T19:46:10.200294Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2311.00117/citation-record","integrity":"/paper/2311.00117/integrity","json":"/paper/2311.00117/citation-record.json","paper":"/paper/2311.00117"},"outbound":[],"paper":{"arxiv_id":"2311.00117","last_updated":"2024-05-28T10:33:03Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T16:41:23.049518Z","submitted_at":"2023-10-31T19:45:15Z","title":"BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.00117."}