{"as_of":"2026-08-11T01:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b0965a8c59e8c68372a29bfedc39265bbfc314f373c9d9b597bd30d1a0203e10","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T14:51:58.722778Z","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":"2026-07-03T16:48:40.485860Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-10T14:51:58.722778Z","title":"Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.14940","last_updated":"2026-06-28T22:17:10Z","snapshot_observed_at":"2026-08-10T14:57:28.038497Z","submitted_at":"2025-01-24T21:55:14Z","title":"CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models","version":4},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-10T14:51:58.722778Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2501.14940"},"observation_digest":"sha256:b295abdf3b0339338128aacbf04ff562815062376b7c260158fc3f15852d20b4","observation_id":"04f5e35a-aceb-478d-8888-eb354d25f5aa","resolution":{"observed_at":"2026-08-10T14:51:58.722778Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-07T14:36:09.355811Z","title":"Embedding-based classiﬁers can detect prompt injection attacks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18333","last_updated":"2025-05-23T19:39:56Z","snapshot_observed_at":"2026-08-07T14:30:46.734293Z","submitted_at":"2025-05-23T19:39:56Z","title":"A Critical Evaluation of Defenses against Prompt Injection Attacks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:36:09.355811Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2505.18333"},"observation_digest":"sha256:732bac14a85ce5c6a78762e508682923d5ba2ae6661d4280a507145e45d3fb50","observation_id":"c3b7a9a3-ed35-42f0-91de-d276a3752d30","resolution":{"observed_at":"2026-08-07T14:36:09.355811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-05T10:44:10.367998Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03787","last_updated":"2025-09-04T00:45:58Z","snapshot_observed_at":"2026-08-08T11:14:03.361977Z","submitted_at":"2025-09-04T00:45:58Z","title":"Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T10:44:10.367998Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2509.03787"},"observation_digest":"sha256:1c8903cba3de91dffae2f7f08fa90ad51865261e52183127d84294887ed83d99","observation_id":"b8102041-b5ed-486b-a1a9-b473682b79f0","resolution":{"observed_at":"2026-08-05T10:44:10.367998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-04T18:34:49.803058Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09912","last_updated":"2025-09-12T00:57:50Z","snapshot_observed_at":"2026-08-06T21:30:11.969868Z","submitted_at":"2025-09-12T00:57:50Z","title":"When Your Reviewer is an LLM: Biases, Divergence, and Prompt Injection Risks in Peer Review","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T18:34:49.803058Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2509.09912"},"observation_digest":"sha256:52b5b60bc92c65eb85e0bf306d50f3b332a023193c18fd3460fecf47d23d0050","observation_id":"f8cb91ea-23c5-4f3f-8bd6-ee69cbcd37ba","resolution":{"observed_at":"2026-08-04T18:34:49.803058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-03T09:53:26.376420Z","title":"Ahsan Ayub and Subhabrata Majumdar","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.12359","last_updated":"2026-01-18T11:33:35Z","snapshot_observed_at":"2026-08-06T10:38:00.882004Z","submitted_at":"2026-01-18T11:33:35Z","title":"Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T09:53:26.376420Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2601.12359"},"observation_digest":"sha256:5a34892f019a05fb94e44c0a5b06b1a0929586d9cee00bbbcbb7b47f663e536b","observation_id":"abdb621b-8e2b-4036-b268-5d4fc8f11237","resolution":{"observed_at":"2026-08-03T09:53:26.376420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2603.15842","last_updated":"2026-05-19T19:10:52Z","snapshot_observed_at":"2026-07-06T22:49:19.323519Z","submitted_at":"2026-03-16T19:17:51Z","title":"Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-21T10:22:04.455412Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2603.15842"},"observation_digest":"sha256:8b64e0e2d53d7283bc6e3886a31f1c0ac833e18ccf16be1189cc6fe49becb67e","observation_id":"c497b8f6-1ad6-415c-9575-13ea48782b6e","resolution":{"observed_at":"2026-05-21T10:24:06.815203Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2604.25562","last_updated":"2026-04-28T12:32:21Z","snapshot_observed_at":"2026-07-06T23:11:25.757664Z","submitted_at":"2026-04-28T12:32:21Z","title":"SnapGuard: Lightweight Prompt Injection Detection for Screenshot-Based Web Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-07T15:48:28.869796Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2604.25562"},"observation_digest":"sha256:e89a24ce1927bc3249cd02d80744eee8d50e4626fd6217a83fbda1ac27bfb0bf","observation_id":"8644cbe2-2eb7-47fd-b3de-881d339eb7ee","resolution":{"observed_at":"2026-05-12T00:06:17.911006Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2604.25716","last_updated":"2026-04-28T14:43:40Z","snapshot_observed_at":"2026-08-08T08:44:13.990356Z","submitted_at":"2026-04-28T14:43:40Z","title":"Cross-Lingual Jailbreak Detection via Semantic Codebooks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-07T16:22:33.567085Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2604.25716"},"observation_digest":"sha256:233723ea6bbe2c71de729d5aea2c4bb742fcd1e827d9867855a66a3cfe219d29","observation_id":"e563db05-895e-4cbf-933d-4168860992be","resolution":{"observed_at":"2026-05-11T23:46:21.951376Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2604.27238","last_updated":"2026-04-29T22:26:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-29T22:26:00Z","title":"SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-07T10:16:07.200458Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2604.27238"},"observation_digest":"sha256:6004723ca11dd8050e7329926d7f97055ba9116b31f0c7818ea5fa3358cfedd3","observation_id":"bee587d4-ef9f-4d8b-aafe-48b70d23e320","resolution":{"observed_at":"2026-05-12T09:36:26.595693Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2606.03136","last_updated":"2026-06-02T04:24:20Z","snapshot_observed_at":"2026-08-06T06:07:51.938149Z","submitted_at":"2026-06-02T04:24:20Z","title":"PsychoPass: Geometric Profiling of Multi-Turn Adversarial LLM Conversations","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T09:55:56.227335Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2606.03136"},"observation_digest":"sha256:36fcd813fe200bc4b7507a501ba185fe9da9a28367ab18450af084280f53b248","observation_id":"5abd07eb-a11f-4a47-9963-acb62c6fef55","resolution":{"observed_at":"2026-07-02T03:36:29.433801Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":"2410.22284","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-07-03T16:48:40.485860Z","title":"Ahsan Ayub and Subhabrata Majumdar.Embedding-based classifiers can detect prompt injection attacks","venue":null,"work_id":"ff206c66-794b-4d28-a0b5-c150fde0b622","year":2024},"citing_paper":{"arxiv_id":"2606.15057","last_updated":"2026-06-19T04:47:48Z","snapshot_observed_at":"2026-08-11T01:00:19.118548Z","submitted_at":"2026-06-13T02:09:08Z","title":"AutoDojo: Adaptive Black-Box Attacks Reveal the Limits of IPI Defenses and Task-Specification Effects in LLM Agents","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T04:57:54.827932Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2606.15057"},"observation_digest":"sha256:0d92d9e49952c8ee5f19cad50b2a83bddc5dad0c82f401c1bc23c0877781d5ba","observation_id":"59b1276c-1746-44dc-943d-fd6922ba8370","resolution":{"observed_at":"2026-07-03T16:48:40.487320Z","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":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-02T01:59:39.957696Z","title":"Sizhe Chen, Julien Piet, Chawin Sitawarin, and David Wagner","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.14493","last_updated":"2026-07-16T02:15:35Z","snapshot_observed_at":"2026-08-09T23:55:59.000200Z","submitted_at":"2026-07-16T02:15:35Z","title":"Context Contamination in LLM Analysis of Network Security Logs: Poison with Passive Prompt Injection and Mitigation Evaluation","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-02T01:59:39.957696Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2607.14493"},"observation_digest":"sha256:668841d131ce9f4451658e94d9c468ef64fc384de5fc7b913846b46f7fde695c","observation_id":"f44342e3-96a8-4a83-a8e6-7d7b55665f01","resolution":{"observed_at":"2026-08-02T01:59:39.957696Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22284","snapshot_observed_at":"2026-08-01T22:55:49.367785Z","title":"Embedding-based classifiers can detect prompt injection attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.15596","last_updated":"2026-08-10T02:18:19Z","snapshot_observed_at":"2026-08-11T01:24:55.247799Z","submitted_at":"2026-07-17T03:44:05Z","title":"From Neural Intent to Cryptographic Authorization: Securing AI-Driven Enterprise Workflows","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T22:55:49.367785Z"},"links":{"cited_paper":"/paper/2410.22284","citing_paper":"/paper/2607.15596"},"observation_digest":"sha256:dcee639b60d8ae4f4c154601e5174c2d2096482f211c57165ba125bfd7b48dc1","observation_id":"a9134d8b-dd2b-4421-8603-ee389873bfdf","resolution":{"observed_at":"2026-08-01T22:55:49.367785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.22284/citation-record","integrity":"/paper/2410.22284/integrity","json":"/paper/2410.22284/citation-record.json","paper":"/paper/2410.22284"},"outbound":[],"paper":{"arxiv_id":"2410.22284","last_updated":"2024-10-29T17:36:59Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T19:41:41.942153Z","submitted_at":"2024-10-29T17:36:59Z","title":"Embedding-based classifiers can detect prompt injection attacks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.22284."}