{"as_of":"2026-08-08T05:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9d3f9c8e24be2e468d8e3f7fa5cbc318a8be10d26296dd7c82c2d37402d7ad92","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:54:12.847460Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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":"2026-08-05T12:54:06.538826Z","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":"2026-07-02T13:26:59.311234Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.04365","snapshot_observed_at":"2026-08-05T12:54:06.538826Z","title":"Attention slipping: A mechanistic understanding of jailbreak attacks and defenses in llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.06982","last_updated":"2025-09-01T04:50:02Z","snapshot_observed_at":"2026-08-07T13:25:33.590193Z","submitted_at":"2025-09-01T04:50:02Z","title":"CARE: Decoding Time Safety Alignment via Rollback and Introspection Intervention","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T12:54:06.538826Z"},"links":{"cited_paper":"/paper/2507.04365","citing_paper":"/paper/2509.06982"},"observation_digest":"sha256:f6086f5444c959a433c25791cbce8646f090685542ba5929e9896a4b9a2319e2","observation_id":"5f1b3b36-483b-4781-ada2-c313b1e68a85","resolution":{"observed_at":"2026-08-05T12:54:06.538826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"cited_work":{"arxiv_id":"2507.04365","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.04365","snapshot_observed_at":"2026-07-02T13:26:59.311234Z","title":"arXiv preprint arXiv:2507.04365 , year=","venue":null,"work_id":"bb50d9f8-e3b6-4c33-9a52-0436a7708350","year":null},"citing_paper":{"arxiv_id":"2606.05609","last_updated":"2026-06-04T02:31:29Z","snapshot_observed_at":"2026-08-05T14:48:48.513078Z","submitted_at":"2026-06-04T02:31:29Z","title":"SlotGCG: Exploiting the Positional Vulnerability in LLMs for Jailbreak Attacks","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-06-28T01:16:07.252429Z"},"links":{"cited_paper":"/paper/2507.04365","citing_paper":"/paper/2606.05609"},"observation_digest":"sha256:70618fe136f4042814b403354edac6bf78a56f7a52d9b70e0986408f24799d60","observation_id":"3c705765-eeba-40e8-95fc-02ca55f8dee6","resolution":{"observed_at":"2026-07-02T13:26:59.312672Z","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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.04365/citation-record","integrity":"/paper/2507.04365/integrity","json":"/paper/2507.04365/citation-record.json","paper":"/paper/2507.04365"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:54:16.674127Z","title":"Bowman, Ethan Perez, Roger B","venue":null,"work_id":"a568288a-5ae0-43ba-949d-3c00cf7b2637","year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.120032Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:b869441cb87df079bdfb32c322f6a684e1492f3ce43ac3860be6cdbabf1def1c","observation_id":"ed19b6ad-0d61-44f6-82e2-19592791cf44","resolution":{"observed_at":"2026-08-06T19:54:16.871531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08419","last_updated":"2024-07-18T18:24:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-12T15:38:28Z","title":"Jailbreaking Black Box Large Language Models in Twenty Queries","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08419","snapshot_observed_at":"2026-08-06T19:54:09.296540Z","title":"Pappas, and Eric Wong","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.296540Z"},"links":{"cited_paper":"/paper/2310.08419","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:1713592e07cfd0fe9c27bd5f772399c8c7e2fc0173f8986a16a3005d8fb67e89","observation_id":"5b845d7d-de3a-4664-96bf-60899d8be88b","resolution":{"observed_at":"2026-08-06T19:54:09.296540Z","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":"2026-08-06T19:54:16.398468Z","title":"Zico Kolter","venue":null,"work_id":"bff8ac3b-fdaa-4e06-9caa-f64576524974","year":2019},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.403630Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:361569bca68877e275207de20e2cbbc16945720dad78e540fdc2f7ff34ddd484","observation_id":"f66d6f79-7d2c-4b13-b5e1-5eb1f2785950","resolution":{"observed_at":"2026-08-06T19:54:16.525171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-06T19:54:09.473833Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.473833Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:cd764124e3ed921bda476832a790d26511b3a97cf46910be24cce4bc143cd4ed","observation_id":"d07ac786-cf88-49bb-96db-b3fbc6d406e1","resolution":{"observed_at":"2026-08-06T19:54:09.473833Z","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":"2026-08-06T19:54:16.147424Z","title":null,"venue":null,"work_id":"bfcaa109-ad3b-4c71-8d81-76670e65e84d","year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.551089Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:e861da7e2246678063ee297dfac124e9e03c20da06a211968508081f97180560","observation_id":"d46fb15d-4d9e-4bac-8e2d-91c6fcac36ae","resolution":{"observed_at":"2026-08-06T19:54:16.254930Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:15.921120Z","title":"Token highlighter: Inspecting and mitigating jailbreak prompts for large language models","venue":null,"work_id":"4e9ea937-605f-4e93-9ff5-b9e6c327d469","year":2025},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.611247Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:cd0eefc6cd1426d30ce384f3da545598ecdeb2c72655f690fc7014c56694391d","observation_id":"48d1a98c-12c5-459b-af6c-feb27d1f27f5","resolution":{"observed_at":"2026-08-06T19:54:16.027866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00614","last_updated":"2023-09-04T17:47:36Z","snapshot_observed_at":"2026-07-06T16:13:23.343694Z","submitted_at":"2023-09-01T17:59:44Z","title":"Baseline Defenses for Adversarial Attacks Against Aligned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.00614","snapshot_observed_at":"2026-08-06T19:54:09.684400Z","title":"Baseline defenses for adversarial attacks against aligned language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.684400Z"},"links":{"cited_paper":"/paper/2309.00614","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:3e8e9afe4e40993b0e1a417088c9b94b29a5d86ef6cc25ff0bd498cd1bff8cf5","observation_id":"bf8fcf33-b58b-4596-9a6d-f3fd30712868","resolution":{"observed_at":"2026-08-06T19:54:09.684400Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:54:09.839439Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.839439Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:0a5a9aefd2c29b834f1df3d373c4a049ff03ad1bbf0b0794910b6c1dd4681524","observation_id":"87b3f59d-53ea-4897-9fb7-2616726aaa25","resolution":{"observed_at":"2026-08-06T19:54:09.839439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04451","last_updated":"2024-03-20T21:34:56Z","snapshot_observed_at":"2026-08-06T02:57:30.438059Z","submitted_at":"2023-10-03T19:44:37Z","title":"AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04451","snapshot_observed_at":"2026-08-06T19:54:09.982978Z","title":"Autodan: Generating stealthy jailbreak prompts on aligned large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:09.982978Z"},"links":{"cited_paper":"/paper/2310.04451","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:f7e6555edb31908b473877af16dffc4aaac3adef027fb6bb82b56a4c211bcd08","observation_id":"65e8a31d-8f11-4111-b10a-3e6f44fddd25","resolution":{"observed_at":"2026-08-06T19:54:09.982978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05206","last_updated":"2026-04-14T16:10:41Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-02T05:14:22Z","title":"Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05206","snapshot_observed_at":"2026-08-06T19:54:10.094408Z","title":"Erfani, Bo Li, Masashi Sugiyama, Dacheng Tao, James Bailey, and Yu-Gang Jiang","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.094408Z"},"links":{"cited_paper":"/paper/2502.05206","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:9dd88704d9456d1caf328441d183f8303ecade0a7bad6fa5ba2e55bea4fa9809","observation_id":"c10190c4-b752-494d-a3d4-1bc75b923637","resolution":{"observed_at":"2026-08-06T19:54:10.094408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.02119","last_updated":"2024-10-31T15:57:42Z","snapshot_observed_at":"2026-07-06T16:56:46.051958Z","submitted_at":"2023-12-04T18:49:23Z","title":"Tree of Attacks: Jailbreaking Black-Box LLMs Automatically","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.02119","snapshot_observed_at":"2026-08-06T19:54:10.231324Z","title":"Tree of attacks: Jailbreaking black-box llms automatically","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.231324Z"},"links":{"cited_paper":"/paper/2312.02119","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:4fda77ec137f72d21bb16960f2841c8bde20eee7025dd254f597f0639cdd325c","observation_id":"46b3415f-05b0-4731-a310-adfb9bc3f1ba","resolution":{"observed_at":"2026-08-06T19:54:10.231324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T19:54:10.352809Z","title":"GPT-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.352809Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:9f74c615113bf8e3ab00e47e3879dc99860e9079e885126bad9d5c537e0150aa","observation_id":"aa504a37-0b53-40b5-90e8-832619a453e6","resolution":{"observed_at":"2026-08-06T19:54:10.352809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03684","last_updated":"2024-06-11T19:02:52Z","snapshot_observed_at":"2026-07-06T16:28:22.350574Z","submitted_at":"2023-10-05T17:01:53Z","title":"SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03684","snapshot_observed_at":"2026-08-06T19:54:10.497216Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.497216Z"},"links":{"cited_paper":"/paper/2310.03684","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:240265f318dcb07bbfa7e063cf757261fa61a7ef24a3c415709827396d94b69e","observation_id":"15698224-46b7-4e96-9c96-bffdb51d7ee5","resolution":{"observed_at":"2026-08-06T19:54:10.497216Z","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":"2026-08-06T19:54:15.654888Z","title":null,"venue":null,"work_id":"da475e1e-b8b5-409e-a0a8-7fe1cc7441be","year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.684287Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:4e3bf89a379337eedd3553a4bf91a84118461270dae83e1bb12d1710abab229a","observation_id":"803559cc-ce6a-414a-801e-0e4e2297a345","resolution":{"observed_at":"2026-08-06T19:54:15.761278Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-06T19:54:10.804884Z","title":"Qwen2.5 technical report","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.804884Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:de0b99d3ef78feda11cd81227bed0bac83d78813620eb85e6288f5d00dcc7c3c","observation_id":"a7a98138-4888-49b4-919a-bd33944a6e4b","resolution":{"observed_at":"2026-08-06T19:54:10.804884Z","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":"2026-08-06T19:54:15.352209Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":"994ae868-e69e-4529-8e57-f3cd6a991369","year":2017},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:10.923995Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:663dc40eccb7645a59c9b94a9fab7cf34efc0c3af3d5fcd567941208772d49cb","observation_id":"34c8d635-0166-48a9-8601-43fe20c4b908","resolution":{"observed_at":"2026-08-06T19:54:15.522650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:15.105517Z","title":"Yu, Qingsong Wen, and Yang Liu","venue":null,"work_id":"0bfab7f1-f946-4b04-9061-99b37b15a8d0","year":2025},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.081110Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:c1c3fa11df53e8a618ba12deefca9eea505f7bf5977e8adc996ea14fb2243760","observation_id":"ed5bec15-6373-4d12-a047-fdc5659bfdd5","resolution":{"observed_at":"2026-08-06T19:54:15.229719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02483","last_updated":"2023-07-05T17:58:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-05T17:58:10Z","title":"Jailbroken: How Does LLM Safety Training Fail?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02483","snapshot_observed_at":"2026-08-06T19:54:11.189415Z","title":"Jailbroken: How does LLM safety training fail? CoRR, abs/2307.02483, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.189415Z"},"links":{"cited_paper":"/paper/2307.02483","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:4c30ae901c78fbdcec879e29892c243293d1991bd280090ab2e61fed96ff769d","observation_id":"5b8c7c9a-59fd-4c5b-854f-6071827ddde2","resolution":{"observed_at":"2026-08-06T19:54:11.189415Z","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":"2026-08-06T19:54:14.858271Z","title":"Defending chatgpt against jailbreak attack via self-reminders","venue":null,"work_id":"dd487db4-0c2c-4457-b405-854b5ad940dc","year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.364637Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:00c0f407c0d395f92974fcc77521cbb711222c6755150a3efc613611ace088dd","observation_id":"281b06a9-2921-4fd4-9b5a-43addc867693","resolution":{"observed_at":"2026-08-06T19:54:14.987500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:14.574125Z","title":"Safedecoding: Defending against jailbreak attacks via safety-aware decoding","venue":null,"work_id":"83e7fe23-a155-4fbe-9399-ce478f76a52f","year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.530520Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:91da076dc30bfffe752b54138e0b1996e8d1da158b710e6df5ba14c4c330cf93","observation_id":"44031e8f-993a-4c66-8791-99f1696146f0","resolution":{"observed_at":"2026-08-06T19:54:14.695109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.04295","last_updated":"2024-08-30T11:57:47Z","snapshot_observed_at":"2026-08-04T23:34:13.332065Z","submitted_at":"2024-07-05T06:57:30Z","title":"Jailbreak Attacks and Defenses Against Large Language Models: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.04295","snapshot_observed_at":"2026-08-06T19:54:11.686321Z","title":"Jailbreak attacks and defenses against large language models: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.686321Z"},"links":{"cited_paper":"/paper/2407.04295","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:80367cb469ecce8faee0deb6cd55b9151e5ca5890c70e07426ba98541e26a5d5","observation_id":"3d4ba01d-58e9-4a56-8fad-03f5838ddbae","resolution":{"observed_at":"2026-08-06T19:54:11.686321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02446","last_updated":"2024-01-27T22:54:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-03T21:30:56Z","title":"Low-Resource Languages Jailbreak GPT-4","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02446","snapshot_observed_at":"2026-08-06T19:54:11.798190Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.798190Z"},"links":{"cited_paper":"/paper/2310.02446","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:8e723cccda5cef0608233237b014e399e82515aa03a3ec6b287f36131edcd3ec","observation_id":"e392ee3c-fb5c-481c-9615-e62c0bd6c656","resolution":{"observed_at":"2026-08-06T19:54:11.798190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.15043","last_updated":"2023-12-20T20:48:57Z","snapshot_observed_at":"2026-07-06T15:59:23.019044Z","submitted_at":"2023-07-27T17:49:12Z","title":"Universal and Transferable Adversarial Attacks on Aligned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15043","snapshot_observed_at":"2026-08-06T19:54:11.959670Z","title":"Attention Sharpening","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:11.959670Z"},"links":{"cited_paper":"/paper/2307.15043","citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:2b5242d1bd07e070264d135e8098ec90c676ac19f9a2eed649d2055c4f355d0e","observation_id":"ba7b66aa-1fbd-4999-9ebd-7bdd9a34e7b0","resolution":{"observed_at":"2026-08-06T19:54:11.959670Z","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":"2026-08-06T19:54:14.309535Z","title":"Each matrix has dimensions d × d, and there are four such matrices: Memory for attention matrices = 4d2","venue":null,"work_id":"cebcf365-644d-4f60-84fd-e735f6fc7e54","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.083145Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:caf611d86cc879c620118c002d243f5bbfe6fe6b2764b16059b6dbb1a51a60eb","observation_id":"046c14d0-ecf8-4438-a0aa-a7d59829a5b7","resolution":{"observed_at":"2026-08-06T19:54:14.418062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:14.035723Z","title":"The first maps the input dimension d to an intermediate dimension 4d, and the second maps back to d","venue":null,"work_id":"8139e293-8f59-4d94-aa11-8f4fca6ec2a8","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.219701Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:472f358a64585d02dfb98727a79142b8b55710084111d917444720ef8afa1903","observation_id":"86198f14-e088-479d-9735-6c0ccc9a442a","resolution":{"observed_at":"2026-08-06T19:54:14.162079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:13.792409Z","title":"With n + m tokens in total (e.g., n input tokens and m output tokens), the memory required for Keys and Values per layer is: Key/Value Memory per layer (bytes) = 4(n + m)d","venue":null,"work_id":"bb6d88a0-7a18-4d7f-8292-0b88992e57d2","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.366585Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:78e6d0b622e1db868bcb6f1e9b87c6e056db89943d3c5fb0cb08ca0b0af00a81","observation_id":"8f7bb32d-8ba1-40fc-a6e7-876053682a09","resolution":{"observed_at":"2026-08-06T19:54:13.924016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:13.575650Z","title":null,"venue":null,"work_id":"0cabbd6c-ee58-47d1-9b57-282d0e55edd1","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.524515Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:4974b8906e75eb0538d55ccedc2aebe0e4c55ee982c3f8ab93cf847e8febc61b","observation_id":"234e7a8c-c05b-45d5-8c90-ef33670f17bb","resolution":{"observed_at":"2026-08-06T19:54:13.681569Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:13.304357Z","title":null,"venue":null,"work_id":"f446c9a1-d91e-4b81-8b03-39c3d80c96af","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.695682Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:99bce530228ccefd3be007565165afccebea784efd444255de8583588f1ee4b6","observation_id":"50d55ebd-4441-4f3a-8d0a-1931f66db025","resolution":{"observed_at":"2026-08-06T19:54:13.410898Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:54:13.107065Z","title":null,"venue":null,"work_id":"a391c7f3-4e80-43ba-a9d3-97c172b1ffb9","year":null},"citing_paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:54:12.847460Z"},"links":{"citing_paper":"/paper/2507.04365"},"observation_digest":"sha256:2bd5520641a235508a611f8127064263d35c1a88b0144c0cf58c29cd5e1b36e4","observation_id":"e9d4c793-97d0-4547-a529-97ef0be96397","resolution":{"observed_at":"2026-08-06T19:54:13.209306Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.04365","last_updated":"2025-07-06T12:19:04Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T19:47:03.672143Z","submitted_at":"2025-07-06T12:19:04Z","title":"Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":0,"verified_fuzzy":10},"total_outbound_references":29},"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 29 of 29 outbound references and 2 inbound Pith citation observations for arXiv:2507.04365."}