{"as_of":"2026-08-17T18:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c4460364a430a762cea04d662b100bdbf6463a6f25bc87a0523208fb201983cd","coverage":[{"denominator":26,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":26,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:30:14.284471Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.05446/citation-record","integrity":"/paper/2506.05446/integrity","json":"/paper/2506.05446/citation-record.json","paper":"/paper/2506.05446"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:30:14.099533Z","title":"Is your prompt safe? investigating prompt injection attacks against open-source llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.099533Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:c08865600732f66a23f633b4e51f6c51305ac7bb65323debbb14f9e7d6eafb55","observation_id":"a785b5d6-6afa-49e3-9432-b1f43fa1d222","resolution":{"observed_at":"2026-08-07T10:30:14.099533Z","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":"2026-08-07T10:30:14.887193Z","title":"alespalla/chatbot_instruction_prompts dataset","venue":null,"work_id":"4cb38daa-7e49-4f40-9c8d-e395eee0fcf3","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.105367Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:24d953777423fd69b15584446561f9475d915e22c59a8c3e235c479cf65e7438","observation_id":"15597410-5c50-47e9-8d40-068e0e986daf","resolution":{"observed_at":"2026-08-07T10:30:14.892925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.117185Z","title":"Evolving security in llms: A study of jailbre ak attacks and defenses","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.117185Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:da19259f5da198ea685912e507585a32b35fd1ecd687d2c167ae3f2fcb78fe2f","observation_id":"f47547fc-3f27-40c9-9dd2-5708ded66ad9","resolution":{"observed_at":"2026-08-07T10:30:14.117185Z","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":"2026-08-07T10:30:14.855629Z","title":"answerdotai/ModernBERT-large model card","venue":null,"work_id":"357ad0c8-10e4-4aef-b5ac-7798596ae3ef","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.122750Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:f854b6c008b9fa8ddb766f32f5135426dd2b42e3bc3424ff5972f825f09363fb","observation_id":"8f83d42f-7862-433c-867d-d70730f10bfa","resolution":{"observed_at":"2026-08-07T10:30:14.860773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.839962Z","title":"Flashattention: Fast and memory- efficient exact attention with io-awareness","venue":null,"work_id":"7170c7c7-a002-41cf-b5f9-522c4041df9f","year":2022},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.135391Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:89de1f53681452ac9e146a8649127d7d1e30697434a2cf07d1a280c02978c25e","observation_id":"a618e34b-a73e-4327-9a65-031e645524c2","resolution":{"observed_at":"2026-08-07T10:30:14.844961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.823057Z","title":"deepset/prompt-injections dataset","venue":null,"work_id":"faa5cb10-b772-4ee3-adae-750b9d690009","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.140855Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:bdd49a823ec69688f79cd6b91354d4b83f515f82bb7db2bc282bc966bea70d5c","observation_id":"ca1fc77a-b177-44a1-8e02-0aa8bc01023e","resolution":{"observed_at":"2026-08-07T10:30:14.828105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.807454Z","title":"Not what you’ve signed up for: Compromising real-world llm-integra ted applications with indirect prompt injection","venue":null,"work_id":"04e1d6be-6854-473f-a580-bacf79e31ba1","year":2023},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.151227Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:5926ff39267ac3c8f9f516ae9e21d882fc68e029edc83ce79662f98e7ceb2f2b","observation_id":"36cf2831-847b-4747-ad85-25283424681c","resolution":{"observed_at":"2026-08-07T10:30:14.812551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.791041Z","title":"Deberta: Decoding-enhanced bert with disen- tangled attention","venue":null,"work_id":"6383d6a0-9b73-4fc8-9e39-140920dc732e","year":2021},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.156957Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:7757b60e8cd35e7797e06b0442933d81fe4d511dbe323bd189ff9dfe1f24644e","observation_id":"eeb39c1a-fb04-4026-b632-0780350dc5ae","resolution":{"observed_at":"2026-08-07T10:30:14.797034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.18510","last_updated":"2024-06-26T17:31:22Z","snapshot_observed_at":"2026-08-16T13:39:21.038674Z","submitted_at":"2024-06-26T17:31:22Z","title":"WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.18510","snapshot_observed_at":"2026-08-07T10:30:14.174388Z","title":"Wildtea ming at scale: From in-the-wild jailbreaks to (adversarially) safer language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.174388Z"},"links":{"cited_paper":"/paper/2406.18510","citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:2430351b819b699519cb771342f09655c8ab3e607aaec9ce6ee119e5ec500f34","observation_id":"87ecb4d9-9701-4136-98fa-3776bfe3a296","resolution":{"observed_at":"2026-08-07T10:30:14.174388Z","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":"2026-08-07T10:30:14.757194Z","title":"lmsys/toxic-chat dataset","venue":null,"work_id":"b960074b-fafd-410c-9a43-1f915355a125","year":2023},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.180653Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:9a5a323e05253875b83c75d3f599364e39ac8608a43e6a1fe97d190e51963b77","observation_id":"1b60db51-a348-4dd8-ab54-2d3f1058cce3","resolution":{"observed_at":"2026-08-07T10:30:14.762653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.773935Z","title":"jackhhao/jailbreak-classification dataset","venue":null,"work_id":"0852627c-4915-4e52-8dea-7d040b2b5ba8","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.164280Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:b6acea0be5da7e231526ace77053f0040761a3c33fcaecea270b0dc39d6e0f22","observation_id":"5493f8f4-21d2-423c-86b0-29dea653c5d1","resolution":{"observed_at":"2026-08-07T10:30:14.780233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09527","last_updated":"2022-11-17T13:43:20Z","snapshot_observed_at":"2026-08-15T06:26:47.552378Z","submitted_at":"2022-11-17T13:43:20Z","title":"Ignore Previous Prompt: Attack Techniques For Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09527","snapshot_observed_at":"2026-08-07T10:30:14.208816Z","title":"Perez and I","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.208816Z"},"links":{"cited_paper":"/paper/2211.09527","citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:be5d1a9ae075aca60f8055273ca4a43a3aa16d74842da895e847eaa25d832baa","observation_id":"19c8f7a4-be45-4a0b-9f1e-11bfd713d954","resolution":{"observed_at":"2026-08-07T10:30:14.208816Z","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":"2026-08-07T10:30:14.701586Z","title":"protectai/deberta-v3-base-prompt-injection model card","venue":null,"work_id":"cec43165-51fe-440c-9f70-be03365aa16d","year":2023},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.214221Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:acfd23fe66261a5578f9060719b97f0582c6974192980e9792fe403328d5bd76","observation_id":"c5219a31-1cc0-4868-8f1b-5401e327c0a6","resolution":{"observed_at":"2026-08-07T10:30:14.707546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.737341Z","title":"microsoft/orca-agentinstruct-1M-v1 dataset","venue":null,"work_id":"1c81b86a-791a-4cff-b284-7df7c8366188","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.186071Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:168c62bae9b0969e32bac6e8bcc5223364811d45e189d798d413b5d1a3b83ef7","observation_id":"466162a8-1efb-4875-95f0-ff871ed7fc01","resolution":{"observed_at":"2026-08-07T10:30:14.743259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.719913Z","title":"OpenSafetyLab/Salad-Data dataset","venue":null,"work_id":"4d5f4f41-cd0c-428f-b088-2485a74ba6d0","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.197333Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:c57635dd0a27a5e954ab383ae7ad048cbd1f63c8722ddeac71b142b29fe34a2d","observation_id":"9adac95b-f1e8-4e6f-8224-760702f8c631","resolution":{"observed_at":"2026-08-07T10:30:14.725493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.593936Z","title":"Do Anything Now","venue":null,"work_id":"c73cf897-39e3-44e6-b06d-e74d6da2324a","year":2024},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.257740Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:4bf0f909f673c4829d628fd1ce8934616f7ea419bf881cfd2d67f1d319175786","observation_id":"4f2b431c-f6ca-4663-aa5d-53dde6c066b0","resolution":{"observed_at":"2026-08-07T10:30:14.599732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.09864","last_updated":"2023-11-08T13:36:32Z","snapshot_observed_at":"2026-08-17T06:56:20.644738Z","submitted_at":"2021-04-20T09:54:06Z","title":"RoFormer: Enhanced Transformer with Rotary Position Embedding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.09864","snapshot_observed_at":"2026-08-07T10:30:14.263630Z","title":"Roformer: Enhanced transformer with rotary position embedding","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.263630Z"},"links":{"cited_paper":"/paper/2104.09864","citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:c13671dfa14ca5cec9b9fa0ac7262327a97966de113939cbf119085ef83e77ab","observation_id":"f5e13ef1-37ee-4912-b75c-db6dbf3a108c","resolution":{"observed_at":"2026-08-07T10:30:14.263630Z","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":"2026-08-07T10:30:14.684768Z","title":"protectai/deberta-v3-base-prompt-injection-v2 model card","venue":null,"work_id":"bb332f6d-ebf9-42c2-8cc0-5dbd86cbf19f","year":2023},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.220366Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:41952eb1e0b577d7e5f4a7e0937c86c7bcf5b3f199bf297a9e38bb22f66e74b6","observation_id":"4136c42e-431c-4f72-8098-676f054e0c0b","resolution":{"observed_at":"2026-08-07T10:30:14.690626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.666542Z","title":"qualifire/Qualifire-prompt-injection-benchmark Dataset","venue":null,"work_id":"67a934e7-6343-48cc-8f6d-1df46388235b","year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.226536Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:024436c1356364a5448be82f8b7bf7beaa02e0d61f1f161202d9ac394d03d0a5","observation_id":"28a7cdaf-448b-4325-b59c-a0f570b5a47e","resolution":{"observed_at":"2026-08-07T10:30:14.672057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.647642Z","title":"qualifire/prompt-injection-sentinel Model Card","venue":null,"work_id":"1550bc32-31df-4266-8251-b8746b5189cb","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.233229Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:92c7571bd8a823b00e98a5fc67d03940dd714013863dc806e8c3e6d1c2581a7b","observation_id":"51adcf6a-515d-402c-a6ea-037be425012c","resolution":{"observed_at":"2026-08-07T10:30:14.653353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.611289Z","title":"reshabhs/SPML-Chatbot-Prompt-Injection dataset","venue":null,"work_id":"a9052a30-be44-4c29-894e-cdf35a188095","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.245204Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:a773d8df9926aa779897f04a0b50cf7b1d38cc639577965efc16246a312444ef","observation_id":"095ff15e-c1ab-4af1-b509-1dd858ea3224","resolution":{"observed_at":"2026-08-07T10:30:14.617335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.576647Z","title":"VMware/open-instruct dataset","venue":null,"work_id":"c17e1f70-e67e-4e19-b2f0-9cce5af42074","year":null},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.269539Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:76b03c6a5ab8bb232991bcbe3a14b414a0c2f2e8db966bfba12ed40c82ceeafa","observation_id":"529255d9-c581-4388-b052-27358ba9f867","resolution":{"observed_at":"2026-08-07T10:30:14.582542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-07T10:30:14.871212Z","title":null,"venue":null,"work_id":"87b5ff84-8188-4ab6-991c-723a6413813c","year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.274423Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:51a6da6468c9193dee8633e3625f5f7825d87fc898f3211e160829ea284d5e8b","observation_id":"1bf8fcfb-e97f-4f87-a270-a0b38866436b","resolution":{"observed_at":"2026-08-07T10:30:14.876023Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13663","last_updated":"2024-12-19T06:32:26Z","snapshot_observed_at":"2026-08-16T17:36:35.256420Z","submitted_at":"2024-12-18T09:39:44Z","title":"Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13663","snapshot_observed_at":"2026-08-07T10:30:14.279458Z","title":"Smarter, better, faster, longer: A mod- ern bidirectional encoder for fast, memory efficient, and lo ng context finetuning and inference","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.279458Z"},"links":{"cited_paper":"/paper/2412.13663","citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:f48e2be68abec35f18813c49692e962b4c6b365c8620ae338bcd85cc8dcc5dc4","observation_id":"72ddb75a-7e99-45e4-914b-9b55344d81f7","resolution":{"observed_at":"2026-08-07T10:30:14.279458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.00843","last_updated":"2025-05-01T20:09:48Z","snapshot_observed_at":"2026-08-17T16:58:08.070567Z","submitted_at":"2025-05-01T20:09:48Z","title":"OET: Optimization-based prompt injection Evaluation Toolkit","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.00843","snapshot_observed_at":"2026-08-07T10:30:14.284471Z","title":"OET: An optimization-based evalua- tion toolkit for benchmarking prompt injection attacks and defenses","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.284471Z"},"links":{"cited_paper":"/paper/2505.00843","citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:5aef4a1ecef521a43c29e453cca4813cfd50a02a46e2fe5cf525be0e37e251bc","observation_id":"533e6e12-6ca0-4dc5-a089-090fc9c83eed","resolution":{"observed_at":"2026-08-07T10:30:14.284471Z","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":"2026-08-07T10:30:14.629353Z","title":"Please update URL if it changes","venue":null,"work_id":"ca264d8e-8b0d-464f-babd-e17e73b55357","year":2025},"citing_paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:14.239307Z"},"links":{"citing_paper":"/paper/2506.05446"},"observation_digest":"sha256:3efce882f84965f19d06c5b48c9c8d05728a3ab5f27946804647c45cf8c1b250","observation_id":"a4f13127-a63d-49d0-992b-0b8d4b1299ff","resolution":{"observed_at":"2026-08-07T10:30:14.634733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.05446","last_updated":"2025-06-05T14:07:15Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-17T16:58:26.986383Z","submitted_at":"2025-06-05T14:07:15Z","title":"Sentinel: SOTA model to protect against prompt injections"},"reference_resolution":{"displayed":26,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":7,"verified_exact":0,"verified_fuzzy":18},"total_outbound_references":26},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2506.05446."}