{"as_of":"2026-08-10T13:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c89b55ed4d24dcdea8cd80391314ca53e69b670895af2879d6c9e37782e8ccb5","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:02:35.374322Z","state":"measured"},{"denominator":27,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":27,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T07:46:24.901516Z","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":"2026-06-30T21:05:04.066789Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2505.16559","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16559","snapshot_observed_at":"2026-06-30T21:05:04.066789Z","title":"Ctrap: Embedding collapse trap to safeguard large language models from harmful fine-tuning","venue":null,"work_id":"2a9d47dd-b0a6-49ea-bdf5-5c2ef406cd21","year":2025},"citing_paper":{"arxiv_id":"2508.20697","last_updated":"2026-08-04T09:31:07Z","snapshot_observed_at":"2026-08-07T23:09:05.524726Z","submitted_at":"2025-08-28T12:07:11Z","title":"Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-18T20:40:44.496392Z"},"links":{"cited_paper":"/paper/2505.16559","citing_paper":"/paper/2508.20697"},"observation_digest":"sha256:514eb12bd9d2799c1ddd7acad8da264e0c61a4b1f00351d8c754622cb5f9c8ae","observation_id":"117067a0-9e10-4a3a-90b8-f3425c596817","resolution":{"observed_at":"2026-05-18T20:41:50.461365Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2505.16559","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16559","snapshot_observed_at":"2026-06-30T21:05:04.066789Z","title":"Ctrap: Embedding collapse trap to safeguard large language models from harmful fine-tuning","venue":null,"work_id":"2a9d47dd-b0a6-49ea-bdf5-5c2ef406cd21","year":2025},"citing_paper":{"arxiv_id":"2605.14605","last_updated":"2026-05-24T08:34:13Z","snapshot_observed_at":"2026-07-06T23:25:58.895612Z","submitted_at":"2026-05-14T09:22:14Z","title":"One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-30T21:01:25.549340Z"},"links":{"cited_paper":"/paper/2505.16559","citing_paper":"/paper/2605.14605"},"observation_digest":"sha256:07e19649c8e0c2731312d6f9bba23719ca1f6924a8c31447d2ae73b8c611efdf","observation_id":"8367f1ff-3e44-4ffa-85af-482337dac97c","resolution":{"observed_at":"2026-06-30T21:05:04.068421Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16559","snapshot_observed_at":"2026-08-01T07:46:24.901516Z","title":"arXiv preprint arXiv:2505.16559 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21356","last_updated":"2026-07-23T14:19:28Z","snapshot_observed_at":"2026-08-07T19:47:51.895704Z","submitted_at":"2026-07-23T14:19:28Z","title":"Emergent Misalignment Recruits a Pre-existing Persona Subspace","version":1},"reference_index":236,"source":"arxiv_source","source_observed_at":"2026-08-01T07:46:24.901516Z"},"links":{"cited_paper":"/paper/2505.16559","citing_paper":"/paper/2607.21356"},"observation_digest":"sha256:ea15d7138b4cdd8a709572445db899fa624ed886d867bd9662b73ce0f9f98bca","observation_id":"39c89248-31c4-49ef-b10c-8831b14fef65","resolution":{"observed_at":"2026-08-01T07:46:24.901516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.16559/citation-record","integrity":"/paper/2505.16559/integrity","json":"/paper/2505.16559/citation-record.json","paper":"/paper/2505.16559"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:37.899834Z","title":"Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper","venue":null,"work_id":"8d06b2af-c0c7-45f7-b227-f01997a13787","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.224927Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:8e4ed5a18404baa1af60613b0663a92ef156facfc6537767e9fd895ffaaf37c6","observation_id":"47eac5f4-625d-49d8-a030-1554e5ee909a","resolution":{"observed_at":"2026-08-07T15:02:37.960991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.755760Z","title":"Guidelines: • The answer NA means that the paper has no limitation while the answer No means that the paper has limitations, but those are not discussed in the paper","venue":null,"work_id":"50d85e9f-ce88-4b4f-b827-658a4baebb29","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.282326Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:1dda5ed9fa01fe3d37583e55cbd2924b82eb1a41cdc0987ebac68ea0f17f0702","observation_id":"fc8b35b5-a7d2-4b17-9f04-d051e690e0b7","resolution":{"observed_at":"2026-08-07T15:02:37.811234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.658028Z","title":"Guidelines: • The answer NA means that the paper does not include theoretical results","venue":null,"work_id":"a944243c-201b-4c11-a168-1d73a611496b","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.333474Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:c4e703c0329b8dcc730c50d95d981d1b9fe7abb606ce7f91af8cc36ca346a277","observation_id":"8990bf3b-8501-47b8-8682-5589519135b9","resolution":{"observed_at":"2026-08-07T15:02:37.684058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-07T15:02:33.819765Z","title":"J., Shen, Y ., Wallis, P., Allen-Zhu, Z., Li, Y ., Wang, S., Wang, L., and Chen, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.819765Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:bd848fab503553346f7bb5237650fcbbe4c87c47d84ecf4250091bbaa21cf15e","observation_id":"e7f5e475-6ba0-425f-a543-7848c54b26d0","resolution":{"observed_at":"2026-08-07T15:02:33.819765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14981","last_updated":"2025-04-16T09:38:09Z","snapshot_observed_at":"2026-07-06T18:49:33.987133Z","submitted_at":"2024-07-20T21:13:56Z","title":"Open Problems in Technical AI Governance","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.14981","snapshot_observed_at":"2026-08-07T15:02:33.948122Z","title":"Open problems in technical ai governance","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.948122Z"},"links":{"cited_paper":"/paper/2407.14981","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:fa17d5af81363b32a2c5abde79bd395337244ff3bfdd24543ae16b15ac4f3c60","observation_id":"bb4026ff-ba31-4594-bd31-a1b658802edc","resolution":{"observed_at":"2026-08-07T15:02:33.948122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12914","last_updated":"2025-02-26T01:01:00Z","snapshot_observed_at":"2026-08-04T16:42:09.474306Z","submitted_at":"2024-09-19T17:10:34Z","title":"Evaluating Defences against Unsafe Feedback in RLHF","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12914","snapshot_observed_at":"2026-08-07T15:02:33.988579Z","title":"Defending against reverse preference attacks is difficult","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.988579Z"},"links":{"cited_paper":"/paper/2409.12914","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:0610d6206b5eaa56796e9264eb520db9f8dc6781f1a8f622309eb660e545625f","observation_id":"e78ab843-a81a-4a19-b7b2-a8e195c0841d","resolution":{"observed_at":"2026-08-07T15:02:33.988579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-07T15:02:34.058916Z","title":"G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahriari, B., Ram´e, A., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.058916Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:4663b9689a8bcf8dd1bd7a61f1f382a2b9b495bb3d7d3a03d34ff436666dd80c","observation_id":"1cbd90fe-224d-45dd-bbd2-4e10f50e66a8","resolution":{"observed_at":"2026-08-07T15:02:34.058916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-07T15:02:34.151266Z","title":"full harmful","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.151266Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:daca3219580b68db56b662eade35ac7234d04512a4e7ec005abf4a37f1f703bf","observation_id":"84298f1d-7dff-4100-973e-0df839cc5d04","resolution":{"observed_at":"2026-08-07T15:02:34.151266Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-07T15:02:36.680423Z","title":"Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics","venue":null,"work_id":"b0f879c0-8af7-4b0d-8c64-2a3e1264fdf3","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.816773Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:b3c801ef39036a0cd5569417420438d376869e636c126d1cf5c08bc2e34ab2bf","observation_id":"1b62cd71-aa38-417c-8a8f-534c1df27f3b","resolution":{"observed_at":"2026-08-07T15:02:36.772259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:36.523894Z","title":"Guidelines: • The answer NA means that there is no societal impact of the work performed","venue":null,"work_id":"9cd276f5-5606-4e8b-bc50-e241404cdf9e","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.916038Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:daa9962b31e320bf52509cd4f744bfbeca6e83dddb1406be7575b8055338bbea","observation_id":"3c4dc9c7-5a88-4f59-94e4-b5ca76daa4e4","resolution":{"observed_at":"2026-08-07T15:02:36.563700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:36.398584Z","title":"Guidelines: • The answer NA means that the paper poses no such risks","venue":null,"work_id":"b989b2a2-eb9d-4387-bb9a-de210c8a8020","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.000232Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:5aa5a1d6171ec02e349f7c248c3662ff7b2281afceb94af5038241fa4416b8cd","observation_id":"f2a6db98-d21d-4027-8f4c-7070736d2c28","resolution":{"observed_at":"2026-08-07T15:02:36.459060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.525597Z","title":"A more detailed version is in Appendix A","venue":null,"work_id":"fb13cf92-9b2e-4813-a66a-d37e37b2def5","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.418173Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:8f00a9f8976e44b51432927065abb0186b98dbf7c8878f51c1cb4343b3b29fb1","observation_id":"12932260-186e-4354-b366-3a7235807a36","resolution":{"observed_at":"2026-08-07T15:02:37.599162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.359755Z","title":"Guidelines: • The answer NA means that paper does not include experiments requiring code","venue":null,"work_id":"2d886b56-3ae2-4d24-9319-b7f0dc36e786","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.559039Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:cbd2fa66e9a55918616a07de87cc48230349ee9466deeaafa2e08c129dd5dfd7","observation_id":"14673d80-893b-4d0a-be1e-be9012348322","resolution":{"observed_at":"2026-08-07T15:02:37.397411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.150334Z","title":"A more detailed version is in Appendix A","venue":null,"work_id":"127fcb97-9019-4186-863f-08b79de059ed","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.614013Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:4bce43ccc8fc655437309de26c177a949e154d79c1ef6a168aaa902220d899aa","observation_id":"8e63675a-aed4-41c8-b6a4-b4e44a93cbdd","resolution":{"observed_at":"2026-08-07T15:02:37.273431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:37.046439Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"cbf1b905-9635-4120-a9cb-3b00b642816c","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.665241Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:a2c65ac43671f0bbe2298768f7816cb7c84a9698291bcc9dabf075e7d7ab72a4","observation_id":"ac28eb24-915c-4f3d-a34d-208d71f0f903","resolution":{"observed_at":"2026-08-07T15:02:37.096302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:36.813711Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"aa6e298c-5d99-49d7-abdd-b92464244c25","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:34.740558Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:743e2fa87f115e633e4e4e800c51164bf9b168769044b2ba8006c0c8ac39e284","observation_id":"5e9f117b-10e3-4ac0-90f9-5e76ebbce63e","resolution":{"observed_at":"2026-08-07T15:02:36.899419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:36.146429Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"51e189ce-4ba8-4bde-9b3a-0b29cb109f6b","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.079947Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:1a1fd05fe08334381493516ecd189b1583a458830e7558a9725c363e877e2252","observation_id":"c513294f-8e28-4519-9b52-c30b3e4d6cf9","resolution":{"observed_at":"2026-08-07T15:02:36.359686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:35.986108Z","title":"Guidelines: • The answer NA means that the paper does not release new assets","venue":null,"work_id":"0106a978-265b-4564-97cd-706b5c1e2266","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.163894Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:94cc44a6a817a0c8849200e008d8cec64ea126ea9c630d9e1a6a6858078c07ea","observation_id":"c9633bff-69c2-4211-836d-22008d98502b","resolution":{"observed_at":"2026-08-07T15:02:36.094759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T15:02:35.858755Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":"8ababf5d-f7d9-43c7-9f0b-e267bbd143f5","year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.239698Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:a86f2ce3f460dbaafe3ecc422a865285495765e8192deced79982d1634e56da2","observation_id":"8f2e6eff-983e-453b-9d64-b5766ce70ee3","resolution":{"observed_at":"2026-08-07T15:02:35.901466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:35.319220Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.319220Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:6e33d702335953ca88c52f4987ab1584ea9a98f64620fcdaa65e799c710ce68a","observation_id":"46dec3ee-c89c-461d-82a1-3ee33660ee97","resolution":{"observed_at":"2026-08-07T15:02:35.319220Z","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":"2026-08-07T15:02:35.658594Z","title":"Answer: [NA] Justification: This research does not incorporate LLMs as any important, original, or non- standard components in its core methodology development","venue":null,"work_id":"b059a48c-4dc4-4ba0-a9d6-e4b7d197aceb","year":2025},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:35.374322Z"},"links":{"citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:e029b7b7aec309e91ccb83b61035284e09e1ef565adb309fa19542e300d19f46","observation_id":"b1210ffd-39ff-49eb-86d1-571cc18f6a94","resolution":{"observed_at":"2026-08-07T15:02:35.722553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04524","last_updated":"2025-02-17T02:32:33Z","snapshot_observed_at":"2026-08-09T21:22:38.867026Z","submitted_at":"2024-10-06T15:34:04Z","title":"Toward Secure Tuning: Mitigating Security Risks from Instruction Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04524","snapshot_observed_at":"2026-08-07T15:02:33.690065Z","title":"Towards secure tuning: Miti- gating security risks arising from benign instruction fine-tuning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.690065Z"},"links":{"cited_paper":"/paper/2410.04524","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:34ac5120a132c2a6b15fe839eaad1dcf7a99b4cec09096d4858f076655eca3cf","observation_id":"945327e5-42c1-4dcd-9ef0-14fb7d36d7b5","resolution":{"observed_at":"2026-08-07T15:02:33.690065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10288","last_updated":"2025-02-28T11:36:06Z","snapshot_observed_at":"2026-07-31T13:57:24.655456Z","submitted_at":"2024-06-12T18:33:11Z","title":"Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10288","snapshot_observed_at":"2026-08-07T15:02:33.756311Z","title":"H., Kumar, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.756311Z"},"links":{"cited_paper":"/paper/2406.10288","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:6e8058e0062d4251c60a29c8916b90ef36c81e6c9ec44bd1c4e87b0ad77c21b1","observation_id":"a033fe85-b3d2-477b-b4a3-7b9377c2a16a","resolution":{"observed_at":"2026-08-07T15:02:33.756311Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07875","last_updated":"2024-03-19T16:50:50Z","snapshot_observed_at":"2026-08-06T23:45:57.910675Z","submitted_at":"2023-09-14T17:23:37Z","title":"Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07875","snapshot_observed_at":"2026-08-07T15:02:33.672549Z","title":"Safety- tuned llamas: Lessons from improving the safety of large language models that follow instructions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T15:02:33.672549Z"},"links":{"cited_paper":"/paper/2309.07875","citing_paper":"/paper/2505.16559"},"observation_digest":"sha256:f25f9038a27d759bb8eccab408a2e237df2d8550a96c3d33be8808f1a0227306","observation_id":"4257c855-f99b-4d55-ae36-2d0b4c91a86b","resolution":{"observed_at":"2026-08-07T15:02:33.672549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.16559","last_updated":"2025-05-22T11:47:08Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-10T03:24:35.944752Z","submitted_at":"2025-05-22T11:47:08Z","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":15},"total_outbound_references":24},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 3 inbound Pith citation observations for arXiv:2505.16559."}