{"as_of":"2026-08-09T22:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:62fe32ee0d701874aa1db6b14c5375e25421b14723303fc3678c97d5f8fbc8cd","coverage":[{"denominator":75,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":75,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:36:58.179549Z","state":"measured"},{"denominator":77,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":77,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-08-03T01:03:28.012736Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07596","snapshot_observed_at":"2026-08-03T01:03:28.012736Z","title":"Twin- break: Jailbreaking llm security alignments based on twin prompts,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.10778","last_updated":"2026-05-29T10:02:55Z","snapshot_observed_at":"2026-08-09T00:41:50.832846Z","submitted_at":"2026-02-11T12:10:14Z","title":"GoodVibe: Security-by-Vibe for LLM-Based Code Generation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T01:03:28.012736Z"},"links":{"cited_paper":"/paper/2506.07596","citing_paper":"/paper/2602.10778"},"observation_digest":"sha256:e4f0479c88b62180cc5dd32cb0fa834c47d7ce2f0ba3638b372e1c7ba0d10669","observation_id":"05abea8d-e50b-41c8-97f6-31c40d0436e9","resolution":{"observed_at":"2026-08-03T01:03:28.012736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"cited_work":{"arxiv_id":"2506.07596","doi":"10.48550/arxiv.2506.07596","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07596","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ArXiv.org","work_id":"644b9e2f-b930-4b92-81aa-dc004ab2e8c6","year":2025},"citing_paper":{"arxiv_id":"2605.09225","last_updated":"2026-05-09T23:51:18Z","snapshot_observed_at":"2026-07-06T23:21:21.560069Z","submitted_at":"2026-05-09T23:51:18Z","title":"The Art of the Jailbreak: Formulating Jailbreak Attacks for LLM Security Beyond Binary Scoring","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-12T02:42:08.565972Z"},"links":{"cited_paper":"/paper/2506.07596","citing_paper":"/paper/2605.09225"},"observation_digest":"sha256:e268579757bad03556039b6726bfa69d42b2f98b6fca36f2295f40d1dd0f1ff9","observation_id":"e5ecc3ab-046e-43dd-a0ba-16e046acb8c0","resolution":{"observed_at":"2026-05-12T02:46:18.596218Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.07596/citation-record","integrity":"/paper/2506.07596/integrity","json":"/paper/2506.07596/citation-record.json","paper":"/paper/2506.07596"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.372046Z","title":"DeepSeek LLM 7B Chat","venue":null,"work_id":"07650266-3f41-47d5-9976-79ac21ce9c7c","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.811450Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:9780073cdcde3488f2b3e2c835abf000afcce3e54acea2992e718875bbbb2af1","observation_id":"c4667882-bb7d-4cfd-85df-ff0099d9668e","resolution":{"observed_at":"2026-08-07T05:36:59.375949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.359236Z","title":"Mistral 7B Instruct v0.2","venue":null,"work_id":"65abc91b-51f2-4dea-bac8-c18d2db51129","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.817870Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:88456b8535d62b46480cd218df3870d23745ca2a0678fadf11790b2376d6ba84","observation_id":"3d7b51bc-6d31-47f2-8e95-ad80061bfea1","resolution":{"observed_at":"2026-08-07T05:36:59.363168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02151","last_updated":"2025-04-17T18:55:45Z","snapshot_observed_at":"2026-08-08T01:18:53.200448Z","submitted_at":"2024-04-02T17:58:27Z","title":"Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02151","snapshot_observed_at":"2026-08-07T05:36:57.822710Z","title":"Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks.arXiv preprint arXiv:2404.02151, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.822710Z"},"links":{"cited_paper":"/paper/2404.02151","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:6cc94f16ff7adac2abf6001c00d2b893c688aea4cb235ed9a186a5c7688f5273","observation_id":"c069bfaa-ee30-474d-a255-197e21c74855","resolution":{"observed_at":"2026-08-07T05:36:57.822710Z","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":"2026-08-07T05:36:59.345299Z","title":null,"venue":null,"work_id":"67fa0e42-8a82-4ba4-b13d-0b7465331677","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.829422Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:764ec395e162e07650182fb006f5c53b7665398731d38288e651e7a46606bdfb","observation_id":"1acdfa2e-b844-4d38-9089-dd432d6eead2","resolution":{"observed_at":"2026-08-07T05:36:59.349778Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.331940Z","title":"Language Models are Few-Shot Learn- ers.NeurIPS, 2020","venue":null,"work_id":"5e61013f-b698-4876-ad9e-236a6e3fd318","year":2020},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.834491Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:a85783a3f78fd6e9f1407da6e4c4d739b82fc91320915941a258e92b1a0770b1","observation_id":"f2d19aa2-596e-4e64-b8d3-bfcfd339d83e","resolution":{"observed_at":"2026-08-07T05:36:59.336081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.317791Z","title":"A review of the application of deep learning in medical image classifica- tion and segmentation.Annals of translational medicine, 2020","venue":null,"work_id":"9b611470-a2c7-435f-b11c-07c63cf9c0aa","year":2020},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.840367Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:48c228fca02a2f5d354ffc89cc4f9899aa6b8e779a7e1a10610c9c39b3989679","observation_id":"a331f1c4-8f63-4135-9629-dcc32f00318b","resolution":{"observed_at":"2026-08-07T05:36:59.322660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.303394Z","title":"Pappas, and Eric Wong","venue":null,"work_id":"2c2c4133-c6af-4187-b308-e2e5eadbda63","year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.845714Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:39dd3f85ef0a6fb3de7245df6a241bf75fc58c5c403d39c808dd8aae597ad74d","observation_id":"0655e8a1-bcb6-4e6a-8913-731f5ce195af","resolution":{"observed_at":"2026-08-07T05:36:59.307761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.290069Z","title":null,"venue":null,"work_id":"300134cc-c4e0-4ba2-8bd1-f0b65d7f4c44","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.850582Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f688fd3ea6226a089a4e6bdbd2ce2915badfa04335a0a798303055599e541b27","observation_id":"6b8b0bce-50ce-4393-be4c-9ae5f8df441e","resolution":{"observed_at":"2026-08-07T05:36:59.294077Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.276770Z","title":"DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving.ICCV, 2015","venue":null,"work_id":"2ba3b2f4-1306-42a1-98ff-765e8d8e0200","year":2015},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.855606Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:353683c77262b785bc71691ed908d0e3a49df038ac6745ca3c1d61ba02805011","observation_id":"f3967756-c0a0-4bf6-bb83-c4028c29d2c7","resolution":{"observed_at":"2026-08-07T05:36:59.281067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:57.860304Z","title":"Finding Safety Neurons in Large Language Models.arXiv preprint arXiv:2406.14144, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.860304Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:a239cb3c7ed87e7fe580d39f09ecf87bfde415cd5ca9b31144abf9e74e7b6b85","observation_id":"ae499608-f5c4-4355-9d51-595d9c438154","resolution":{"observed_at":"2026-08-07T05:36:57.860304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05457","last_updated":"2018-03-14T18:04:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-03-14T18:04:21Z","title":"Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.05457","snapshot_observed_at":"2026-08-07T05:36:57.865187Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.865187Z"},"links":{"cited_paper":"/paper/1803.05457","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:cc99f4940c88250c9341eb7a676445c4fa14feeb844422f5954ced1a0efb8072","observation_id":"fad7322a-2904-413d-a846-f0a374e9ed92","resolution":{"observed_at":"2026-08-07T05:36:57.865187Z","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":"2026-08-07T05:36:59.263073Z","title":"Natural language processing (almost) from scratch.JMLR, 2011","venue":null,"work_id":"425fd1e6-f40d-405c-a2e4-5e8d056d396a","year":2011},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.872050Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:21a7f203d9a143a25f8359c1de4dfb03959ce8cc43f49c57893baf0996b5bacf","observation_id":"932cb4ec-7843-46b8-b39b-05682e2d5e9e","resolution":{"observed_at":"2026-08-07T05:36:59.267292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02954","last_updated":"2024-01-05T18:59:13Z","snapshot_observed_at":"2026-08-02T13:11:16.882565Z","submitted_at":"2024-01-05T18:59:13Z","title":"DeepSeek LLM: Scaling Open-Source Language Models with Longtermism","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02954","snapshot_observed_at":"2026-08-07T05:36:57.876865Z","title":"DeepSeek LLM: Scal- ing Open-Source Language Models with Longtermism","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.876865Z"},"links":{"cited_paper":"/paper/2401.02954","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:1c534b2b81a032a3823bad0e07acf8da13ad56d6f564a47957f300be246da070","observation_id":"cc1c97ba-0ad4-4583-ab56-b3d1a3c3fae6","resolution":{"observed_at":"2026-08-07T05:36:57.876865Z","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":"2026-08-07T05:36:59.249609Z","title":null,"venue":null,"work_id":"74c20a9f-2cb2-4f83-9db4-e1ee166927a4","year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.882154Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:9d2dc452e4ef63f32d60f18461a23d45142d0389291eac7439d8578650142820","observation_id":"f7328520-9651-4cc2-8ba3-00c44b3ec280","resolution":{"observed_at":"2026-08-07T05:36:59.254081Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.235696Z","title":"BERT: Pre-training of Deep Bidi- rectional Transformers for Language Understanding","venue":null,"work_id":"d6f3b2de-ccde-4c16-8bd0-e6f378578246","year":2019},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.886676Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:cff894ce3c842424c91292cd9242f0744d66de7eb0eb65463948001469b97725","observation_id":"57aaf956-792b-4db4-9ad4-2785be8e1762","resolution":{"observed_at":"2026-08-07T05:36:59.240256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.222219Z","title":null,"venue":null,"work_id":"3079a819-3492-4be4-982c-4e29c7f3cf20","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.891373Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:5cc92be813b5b94c3c3f521249b099c789d43416e768df1b13a82a49afc635ba","observation_id":"42cb55e0-6667-4d2d-8093-0bfbe573e7a7","resolution":{"observed_at":"2026-08-07T05:36:59.226412Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.209198Z","title":"Gemma 2 27B Instruction Tuned","venue":null,"work_id":"e0fd4e6c-07e8-45d2-8141-fe3bfd4ac8fa","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.896914Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:6b832c68c9b9ecc579e94fe3e66c2ddbe81ee39922cc5d89750148de3b0ec994","observation_id":"c4863368-b26d-416d-baef-3730e1746f6a","resolution":{"observed_at":"2026-08-07T05:36:59.213377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.195479Z","title":"Gemma 2 2B Instruction Tuned","venue":null,"work_id":"3bb570e3-affc-40f3-be6e-d36135129f45","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.901664Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:26ab6208fd7aafd1638b5de672702251bba672a0e965d868e9d3c1f087b58998","observation_id":"30fc7dca-2646-47ee-8ab8-a4d3c2da007a","resolution":{"observed_at":"2026-08-07T05:36:59.199591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.181070Z","title":"Gemma 2 9B Instruction Tuned","venue":null,"work_id":"d45af05d-c6fe-4afd-b985-aa29ff033383","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.906402Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:4d29c0bc0bf1a2ba9ea9cefcb40fe10e91a19c9242e3ba3bf131dd426e3ae8e4","observation_id":"200dba93-d003-4897-8520-44ece877a7c7","resolution":{"observed_at":"2026-08-07T05:36:59.185368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.167041Z","title":"Gemma 3 1B Instruction Tuned","venue":null,"work_id":"9905d085-4bbc-46a5-b6be-f3f6125c6465","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.911405Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:8fa4c39f46966ecf14bf6d18bb1c0f87031fb766d68ec5ed1582665f89d38053","observation_id":"1464180f-c9d3-4464-b93f-f2275742024a","resolution":{"observed_at":"2026-08-07T05:36:59.171365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.08295","last_updated":"2024-04-16T12:52:47Z","snapshot_observed_at":"2026-08-03T03:29:01.959523Z","submitted_at":"2024-03-13T06:59:16Z","title":"Gemma: Open Models Based on Gemini Research and Technology","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.08295","snapshot_observed_at":"2026-08-07T05:36:57.915684Z","title":"Gemma 2: Open Models Based on Gemini Research and Technology.arXiv preprint arXiv:2403.08295, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.915684Z"},"links":{"cited_paper":"/paper/2403.08295","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:db2db0223865ffd96d78b8fb8b41461eeb868cd059425d412be65a781a7a5243","observation_id":"bdd14b95-6036-4ae1-a189-075d134d296d","resolution":{"observed_at":"2026-08-07T05:36:57.915684Z","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":"2026-08-07T05:36:59.152629Z","title":"Qwen 2.5 14B Instruct","venue":null,"work_id":"e758187c-85ea-4de1-ac19-c3fb4bd3a848","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.920689Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:00fa83907953153020dcc9f3a88c3b19dcd682c2cd69b2880274a8fc94ea465b","observation_id":"431344a7-d44f-4f3a-bf82-d595cbc63baf","resolution":{"observed_at":"2026-08-07T05:36:59.157128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.138195Z","title":"Qwen 2.5 32B Instruct","venue":null,"work_id":"d3fea542-5caf-4790-93a9-1b44425d5794","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.925225Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:24a97f019e11bf24bed3c9a0bf0a3a39dbe08034d85a213f6af3acbb1aa7f1c7","observation_id":"b7c66642-f910-40c4-91bd-ab7449e7134e","resolution":{"observed_at":"2026-08-07T05:36:59.142520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.121448Z","title":"Qwen 2.5 3B Instruct","venue":null,"work_id":"3bcc8ef2-5b01-4755-af6d-161e0a9889ae","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.930164Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:a8a1dd8cf7880a1f979097fa3b3e2768c509707df96fca2cf1893ab90cd11726","observation_id":"4c59e1ed-02f6-457d-aa21-46947755431a","resolution":{"observed_at":"2026-08-07T05:36:59.127811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.105598Z","title":"Qwen 2.5 72B Instruct","venue":null,"work_id":"ceabc88c-3720-4ac7-ba15-678c30b569e3","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.934919Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:ea51f4d7ebb1f0227824195d0b0e5e3081ba5633ada1797cb118f59b9ad4ee5d","observation_id":"9c172ed8-f26e-49c7-a4e6-da1b4df6fe5e","resolution":{"observed_at":"2026-08-07T05:36:59.110308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.091745Z","title":"Qwen 2.5 7B Instruct","venue":null,"work_id":"82fe59c3-28c0-4469-8625-d373a450d8e4","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.939480Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:ff01cb1151ca59d8e3739bf13b1c3f28f12be6407dca5a6e02a876117249be9d","observation_id":"1d7656d8-32cf-4e92-9408-ccdd39a76e4f","resolution":{"observed_at":"2026-08-07T05:36:59.095820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.06733","last_updated":"2019-03-11T20:45:33Z","snapshot_observed_at":"2026-07-06T05:56:16.413472Z","submitted_at":"2017-08-22T17:31:54Z","title":"BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.06733","snapshot_observed_at":"2026-08-07T05:36:57.943727Z","title":"BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.arXiv preprint arXiv:1708.06733, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.943727Z"},"links":{"cited_paper":"/paper/1708.06733","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:60777907dbbca35864ae4c32bbab0b03c77b45296af8c76b822ad9b05cefca06","observation_id":"bbb9fb27-09b9-430d-a1b3-7d721c7a8dca","resolution":{"observed_at":"2026-08-07T05:36:57.943727Z","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":"2026-08-07T05:36:59.078380Z","title":"Gradient-based Adversarial Attacks against Text Transformers.EMNLP, 2021","venue":null,"work_id":"cd432fb1-57ce-4535-aa54-7e51052b5f75","year":2021},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.949358Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:1c0192ebf0b8d847d65ae84651df8bea59be6df55c4f444255a9a35e72025b84","observation_id":"a738dcef-d76c-4ae6-be27-07bea86ff41c","resolution":{"observed_at":"2026-08-07T05:36:59.082522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.065503Z","title":"Hugging Face","venue":null,"work_id":"b7d483c5-1646-44e3-ad10-202ca70d7132","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.954300Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:1e7f31061384d750acace70a1680e87d0327907d5ee682ad20456f7d80a7f8c7","observation_id":"64e0cd0e-73e9-4e3e-8b36-c9d254f5faad","resolution":{"observed_at":"2026-08-07T05:36:59.069582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-07T05:36:57.959074Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.959074Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:43f579162e9ce8d6163c3b2a7d6b97ecf0dee9a222464779aad31a7217420e9f","observation_id":"748dbe20-cb50-49e2-a38a-ab0b7eac7bc3","resolution":{"observed_at":"2026-08-07T05:36:57.959074Z","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":"2026-08-07T05:36:59.052094Z","title":"Kaggle: Your Home for Data Science","venue":null,"work_id":"9de819f5-1901-452e-8107-5852957d8723","year":null},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.963888Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:3dfdcfe69a1d58b68e0214bf1669926797dab716e749df05f63531d3fb876576","observation_id":"7a98b255-044c-4f91-9418-8c11c29573d3","resolution":{"observed_at":"2026-08-07T05:36:59.056619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.038800Z","title":"Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks.IEEE SPW, 2024","venue":null,"work_id":"c89314fb-dc94-476d-8d21-0932cb97a5c1","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.968436Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:179c8c5541e33c73e3988580c4b35ebac9ff6c6778d1c492d59abff5929e89ce","observation_id":"43d0d9ca-796d-4538-9d5a-e15e259e16e5","resolution":{"observed_at":"2026-08-07T05:36:59.043152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.024680Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts.USENIX Security, 2025","venue":null,"work_id":"971e525f-0877-4ded-b472-a50f14f5456c","year":2025},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.973333Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:a6d74ee9baccb6558490d63d9cbb6e9dde38c1a9c5407b01cf800cf54be995c2","observation_id":"235d7e53-e848-4e48-a9ea-61b50c1785c7","resolution":{"observed_at":"2026-08-07T05:36:59.029104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:59.011463Z","title":"SentencePiece: A simple and language-independent subword tokenizer and detokenizer for Neural Text Processing.EMNLP, 2018","venue":null,"work_id":"a878a219-0e95-41d6-b5a0-4e136f61a57e","year":2018},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.978178Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:05bc6cbc12bf266eebc5e552c46517e1ecad07251fd4a7e4b5ad5bb6a96c83b0","observation_id":"af9b9e39-8dc0-4736-8177-cb71e19cf6d6","resolution":{"observed_at":"2026-08-07T05:36:59.016149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.998561Z","title":null,"venue":null,"work_id":"0661a8a7-771d-42b7-a296-a14ce11b6637","year":2019},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.982656Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:55a46ba8bf1729547c33991dd4c5e24ec3c7452e9ccc22cee3c08b0d36d4647f","observation_id":"3ca1d9e0-2426-4105-a641-d716a1143aef","resolution":{"observed_at":"2026-08-07T05:36:59.002599Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.985096Z","title":"Backdoor Learning: A Survey.IEEE Transactions on Neural Networks and Learning Systems, 2022","venue":null,"work_id":"5f67b5c8-a194-4ea0-95db-3fc4813f6e3d","year":2022},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.987594Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:fe5bebe4c4b55b81d0b9ef124aa9a69ddb4b2148671c79ec1d29a2eed513d049","observation_id":"a4bf452f-dc18-4ae3-a9c0-0c89bd18d61a","resolution":{"observed_at":"2026-08-07T05:36:58.989392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.970785Z","title":"AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.ICLR, 2024","venue":null,"work_id":"db248c3f-fd67-4488-b8a4-2cfbe81ffcbb","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.992623Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:dd844520573ba9f56df865ab978fbf1e8f8b55c7901c9c329e61cd4fde6df5aa","observation_id":"46d91521-766a-42a7-8fc2-d4c8953ad6a5","resolution":{"observed_at":"2026-08-07T05:36:58.975576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05499","last_updated":"2025-12-29T02:25:27Z","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-08T18:43:11Z","title":"Prompt Injection attack against LLM-integrated Applications","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05499","snapshot_observed_at":"2026-08-07T05:36:57.997650Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:57.997650Z"},"links":{"cited_paper":"/paper/2306.05499","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f97fae288a362e4a56a8674a88d71caf8ce4fd5a62d4200374c3b13f953b6601","observation_id":"b44450f2-c569-40fa-9b84-495b8ccdc68b","resolution":{"observed_at":"2026-08-07T05:36:57.997650Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04249","last_updated":"2024-02-27T04:43:08Z","snapshot_observed_at":"2026-07-06T17:26:23.067923Z","submitted_at":"2024-02-06T18:59:08Z","title":"HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04249","snapshot_observed_at":"2026-08-07T05:36:58.003299Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.003299Z"},"links":{"cited_paper":"/paper/2402.04249","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f3aeec7c7ab81a8e14e6924d69d687517fc6accd473f7ce30f7f380b16040c98","observation_id":"419a786a-5820-4356-8525-bf33c695aa41","resolution":{"observed_at":"2026-08-07T05:36:58.003299Z","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":"2026-08-07T05:36:58.956623Z","title":"Llama 2 13B Chat","venue":null,"work_id":"5a879cbd-c799-4d4c-ae7d-f283ceb1f43a","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.008876Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:617740321b18ecee9bf4f794850d2728b4eabe0787e39f0448637eaa5f6d6195","observation_id":"c522ee51-582c-4774-8227-eea8ba257110","resolution":{"observed_at":"2026-08-07T05:36:58.960942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.943014Z","title":"Llama 2 70B Chat","venue":null,"work_id":"d1ffbf79-b64e-4139-a840-871a18801082","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.013382Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:0b3658acd7f192b7f223ebf68131d67207f3a63274a6ad2ae17dc51953dd34fd","observation_id":"1b48a51d-a368-4e5b-9b0c-4e9c641c6535","resolution":{"observed_at":"2026-08-07T05:36:58.947422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.929385Z","title":"Llama 2 7B Chat","venue":null,"work_id":"c1e713c5-91d7-41c3-926b-57a19a1cb0aa","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.018626Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:421535cd62367e0414638ae466cff064efd17909c5f6a3295a245459a55d6c1d","observation_id":"5c1a7478-a653-487b-9896-6be0a84ccd9c","resolution":{"observed_at":"2026-08-07T05:36:58.933489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.915141Z","title":"Llama 3.1 8B Instruct","venue":null,"work_id":"7a5c7d83-b7bc-42a9-9741-c187a2b09e82","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.023583Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:932384af3c309f9f75b2864dd506be9aef135b037956538785dab9df2397e9df","observation_id":"81429a98-3c39-4cd1-bb79-804aabad1ffc","resolution":{"observed_at":"2026-08-07T05:36:58.919872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.900862Z","title":"Llama 3.3 70B Instruct","venue":null,"work_id":"f90af2d3-0113-4700-aeb9-b3747f0a61df","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.028769Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:82a6e1640657b817c626e574f66db15862e9f75f93062ddb86e2f078d9bdaf7c","observation_id":"50edf83d-8106-4130-9231-a9a0265b565a","resolution":{"observed_at":"2026-08-07T05:36:58.905409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.887209Z","title":"Llama guard 3 8b","venue":null,"work_id":"0e828e76-7da3-40a9-8d7d-f8a42588076c","year":2025},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.033447Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:b3c413238b4e766316420664028827f033107fefb2353d0a7a57dfc22b4ab2a3","observation_id":"1d7dd1f0-a501-46db-a3bf-621a22213e6a","resolution":{"observed_at":"2026-08-07T05:36:58.891368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.872647Z","title":"Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering","venue":null,"work_id":"f8dae38e-d37a-4a28-9c92-31134bde76cb","year":2018},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.038169Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:562a13f17f69e378c5879f3f156b4c783c2372486fe0aa5a013e88870c528c95","observation_id":"87a12934-7594-48a7-8688-d537ea6f7c18","resolution":{"observed_at":"2026-08-07T05:36:58.877252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.857645Z","title":null,"venue":null,"work_id":"09358cba-cacc-4006-8f21-d5320a5334ff","year":2020},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.042801Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:acea049122c8242d6a2b2938e92ad6973122e3d5fea19c44fc70986885cb87ae","observation_id":"0b2320a8-d09f-4b73-8953-30b083ddc985","resolution":{"observed_at":"2026-08-07T05:36:58.862074Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-07T05:36:58.047377Z","title":"GPT-4 Technical Report.arXiv preprint arXiv:2303.08774, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.047377Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f4b983d307b10ad8df679222c62f504d44869fecee2c3e65a2eebcab76950b0b","observation_id":"0854fd31-d5f6-4687-81c9-55f03057c7a1","resolution":{"observed_at":"2026-08-07T05:36:58.047377Z","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":"2026-08-07T05:36:58.842295Z","title":null,"venue":null,"work_id":"c815f4e4-25bc-4c42-ad91-b3db1fb368e7","year":2019},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.053038Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:017e6d39748bd216866c660d1b4998b2657bcb8140c0181dc575331833188716","observation_id":"09546edd-6355-4941-9fbd-550e64cccb87","resolution":{"observed_at":"2026-08-07T05:36:58.847174Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01606","last_updated":"2024-10-02T14:47:05Z","snapshot_observed_at":"2026-08-03T19:54:21.584740Z","submitted_at":"2024-10-02T14:47:05Z","title":"Automated Red Teaming with GOAT: the Generative Offensive Agent Tester","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01606","snapshot_observed_at":"2026-08-07T05:36:58.057842Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.057842Z"},"links":{"cited_paper":"/paper/2410.01606","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:e638e168dbcbbf10f28bbd9b31986c518412598dc8c76ba2c9ccf028d928482a","observation_id":"1dc111cf-1c33-438d-9d62-2d807d3fca6a","resolution":{"observed_at":"2026-08-07T05:36:58.057842Z","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":"2026-08-07T05:36:58.825515Z","title":"Gradient Descent","venue":null,"work_id":"899cf14f-6ab0-4e75-b46c-f2b2afbafdf4","year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.062774Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:27fa904b7ce13677a3c735667227ac3429c63d3e4bb687cf56abb8e597e5d67a","observation_id":"1fd41837-867c-4e8b-9394-03d60eb485a8","resolution":{"observed_at":"2026-08-07T05:36:58.830890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.810270Z","title":null,"venue":null,"work_id":"2945b5a4-a565-4a86-b002-a637fc8a0e48","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.067654Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:4f3ff52686cd76c4ebc9d8421cc76b185dc713054cbafc1906106c08558f76ea","observation_id":"ed92a7e7-6207-4378-b555-6d3d17790395","resolution":{"observed_at":"2026-08-07T05:36:58.814992Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T05:36:58.072430Z","title":"The Llama 3 Herd of Models.arXiv preprint arXiv:2407.21783, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.072430Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:e06597c101e27a5bffd16f37a2c302cb005f9c9d62ee4f81c7e7d7aa9de1d0c5","observation_id":"56c857bd-92be-4fc8-ae18-dda51f1f0073","resolution":{"observed_at":"2026-08-07T05:36:58.072430Z","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":"2026-08-07T05:36:58.795740Z","title":"WinoGrande: An Adversarial Winograd Schema Challenge at Scale.AAAI, 2020","venue":null,"work_id":"2a92a28d-a438-43c5-ae85-706ae2c403de","year":2020},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.077206Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:4f956625b2f2dc61e7e797b17edc396a7a04d658bce8666cf8221492be4a714d","observation_id":"fd0fe736-56e2-4922-9f49-3afeba09c9cc","resolution":{"observed_at":"2026-08-07T05:36:58.800197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.780870Z","title":"Neural Machine Translation of Rare Words with Sub- word Units.ACL, 2016","venue":null,"work_id":"be2c004b-79c3-4c99-9be6-30e354f830f9","year":2016},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.081943Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:e9523c58035d9357fd1599ccc29d472152f87cfb6c76f60f70c0c682afcbb501","observation_id":"6a8ebfe2-3fcc-4bb2-be3f-749b3a309df3","resolution":{"observed_at":"2026-08-07T05:36:58.785772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.03825","last_updated":"2024-05-15T12:06:31Z","snapshot_observed_at":"2026-07-06T16:03:34.432602Z","submitted_at":"2023-08-07T16:55:20Z","title":"\"Do Anything Now\": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.03825","snapshot_observed_at":"2026-08-07T05:36:58.086467Z","title":"Do Anything Now","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.086467Z"},"links":{"cited_paper":"/paper/2308.03825","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:c5977687419516d24a019ea19f9a9c4d8b0c4bcd4cdce02efb5a43e702a33c4a","observation_id":"c88a7991-a998-4bd2-bcc7-971a4a59e63b","resolution":{"observed_at":"2026-08-07T05:36:58.086467Z","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":"2026-08-07T05:36:58.766482Z","title":null,"venue":null,"work_id":"542f5915-b308-4fc8-aaa7-88742b2bf2c0","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.091409Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f4a86efcfe9a4a2d06da42408eabd5491cb32e30015d983f06addd9104554e77","observation_id":"dd6b4dc9-8314-4cda-85af-50ffce4abdf8","resolution":{"observed_at":"2026-08-07T05:36:58.770882Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.095917Z","title":"Gemma, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.095917Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:eb5be3046a0b140c1e0d4aef20ce7003eca95d918a333be63455d9f29b914caa","observation_id":"67c4dc04-fa81-445b-a13e-1a5e73ed3713","resolution":{"observed_at":"2026-08-07T05:36:58.095917Z","resolver_source":null,"status":"parse_uncertain"},"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":"2026-08-07T05:36:58.100779Z","title":"Gemma 3, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.100779Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:060fbc3e77a15e4b18adf1cebc56b999c7aa71bedd4812d86f0612a247fb454c","observation_id":"fbdaf693-0569-42be-84f7-2153f8c0e3c8","resolution":{"observed_at":"2026-08-07T05:36:58.100779Z","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":"2026-08-07T05:36:58.733441Z","title":"Pytorch, 2022","venue":null,"work_id":"583f8410-f84d-482b-a4c4-2a860bdf9064","year":2022},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.105708Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:19583108843de70d73350919a0083d7078f1a786c4a580cb0f1663872c06c509","observation_id":"b1d25097-5d47-4f4f-b981-161f50c9f53d","resolution":{"observed_at":"2026-08-07T05:36:58.737769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-07T05:36:58.110690Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.110690Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:565d67f6434a37c54700f3dcf1a1c29978cd8734be7aa66c74fbc02a3d458222","observation_id":"c603f4e8-17d7-4a05-89c1-5945d2ef7818","resolution":{"observed_at":"2026-08-07T05:36:58.110690Z","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":"2026-08-07T05:36:58.719822Z","title":"Centrum voor Wiskunde en Informatica Amsterdam, 1995","venue":null,"work_id":"ea980abd-dbee-44b3-8a9f-8feb7cb39b20","year":1995},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.115965Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:c47aa104efa000f85056310ed782f20257621b9bf727d91a26886a354005c1d8","observation_id":"5c1526ad-f5be-484f-98e7-2573dd02add4","resolution":{"observed_at":"2026-08-07T05:36:58.724100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.704265Z","title":null,"venue":null,"work_id":"f61573cd-6d55-4fa4-b037-915eb964db13","year":2017},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.120844Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:1699fbe0cf05700f61478fb895e076269df876361e8e3ba3bfbc1b034cfdf4e3","observation_id":"a18405a5-5cfc-4230-9522-61f54cb7fb90","resolution":{"observed_at":"2026-08-07T05:36:58.708640Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.690062Z","title":"A Simple and Effective Pruning Approach for Large Language Models.ICLR, 2024","venue":null,"work_id":"8c5f9753-53c9-4791-98ff-170cd5888a7f","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.126111Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:12b165ab163211e0ed1c196fc632733bee750fd5841e17cdf4198b5a441bb7cd","observation_id":"36195b31-1a83-48f9-9e28-ac244d5ee814","resolution":{"observed_at":"2026-08-07T05:36:58.694479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.676661Z","title":null,"venue":null,"work_id":"5754b192-fcfe-4046-a286-d6b5141e31cc","year":2019},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.131255Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:f74028a4de2a9701e4f9bd74b4e35c709b27e1ac358096d43ea2cc27ca1087b4","observation_id":"5dd3082f-e0aa-48dd-a03a-1d576f8b1046","resolution":{"observed_at":"2026-08-07T05:36:58.680727Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06387","last_updated":"2024-05-25T07:01:15Z","snapshot_observed_at":"2026-08-06T13:25:52.403871Z","submitted_at":"2023-10-10T07:50:29Z","title":"Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06387","snapshot_observed_at":"2026-08-07T05:36:58.135736Z","title":"Jail- break and Guard Aligned Language Models with Only Few In-Context Demonstrations.arXiv preprint arXiv:2310.06387, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.135736Z"},"links":{"cited_paper":"/paper/2310.06387","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:ebea07f972fc067d4960e17521005984069734c44a510390c4b274225cb89e69","observation_id":"abd6921c-f91f-4c0e-b1af-47bf8baa381a","resolution":{"observed_at":"2026-08-07T05:36:58.135736Z","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":"2026-08-07T05:36:58.660831Z","title":null,"venue":null,"work_id":"1be65720-76d3-4f0b-a120-a44fbffc8881","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.140272Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:d2d0968f3922cf1b8930e7242df79dc3028ddc3f36c6418bf3ee889ff9ec8d9b","observation_id":"fc70e041-e9e1-4943-9760-4bb594bbb20a","resolution":{"observed_at":"2026-08-07T05:36:58.665664Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-07T05:36:58.144812Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.144812Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:751b04f02266f79a48050a0c5efe1f65dae99eec06a4d1c4ceab1166cccaf8ff","observation_id":"7b986524-8426-48e8-97f4-b410817e86b7","resolution":{"observed_at":"2026-08-07T05:36:58.144812Z","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":"2026-08-07T05:36:58.645799Z","title":null,"venue":null,"work_id":"671bc004-c6ba-4ee3-88e1-950304b4f8e6","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.149800Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:7da0876f50d84effa3f12bed1b638ebed32468f83f52751084109e157ef72014","observation_id":"b633371f-6db0-4379-ac16-8d75271362fb","resolution":{"observed_at":"2026-08-07T05:36:58.650035Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.630906Z","title":"NLSR: Neuron-Level Safety Realignment of Large Language Models Against Harmful Fine-Tuning.AAAI, 2025","venue":null,"work_id":"af802eac-9217-4828-a582-85f21ddcc489","year":2025},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.154405Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:c8643893d1c3cf302f4f611a81b3e22b918ff7146963a393ba6778df5ba3bcfe","observation_id":"e7482177-de9c-4389-931c-da572ce734cc","resolution":{"observed_at":"2026-08-07T05:36:58.635315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10253","last_updated":"2024-06-27T16:01:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-19T02:19:48Z","title":"GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10253","snapshot_observed_at":"2026-08-07T05:36:58.160681Z","title":"GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts.arXiv preprint arXiv:2309.10253, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.160681Z"},"links":{"cited_paper":"/paper/2309.10253","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:d5638544b977fe27390b8ae1a586918003f612cfce946a34ecfc715901a0bd12","observation_id":"1286cca4-608d-45a7-baef-af7346ed68bf","resolution":{"observed_at":"2026-08-07T05:36:58.160681Z","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":"2026-08-07T05:36:58.616451Z","title":"HellaSwag: Can a Machine Really Finish Your Sentence?ACL, 2019","venue":null,"work_id":"ddf32528-ae3d-466e-b46d-690ddf3c8d56","year":2019},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.165507Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:09245380a06f0c0d42889171c5a989fde573fac086280b028ab7fa2648a90fcc","observation_id":"3cb4a1b2-dfd7-4561-9f38-162b82ca55fc","resolution":{"observed_at":"2026-08-07T05:36:58.621030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.601520Z","title":"How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs.ACL ARR, 2024","venue":null,"work_id":"ed0ce2f4-2219-4917-9f18-01293f55a3b7","year":2024},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.170255Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:7bf5f0b171c2dad786b0c06abc4dff75aa5e053a195ee3a970611af097cc38a6","observation_id":"09e75c66-8e2c-4d85-b9a2-3bdd3d676cf6","resolution":{"observed_at":"2026-08-07T05:36:58.606730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:58.583732Z","title":"Understanding and Enhancing Safety Mechanisms of LLMs via Safety- Specific Neuron.ICLR, 2025","venue":null,"work_id":"4dd62e47-fd54-410a-a574-51548decd074","year":2025},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.174845Z"},"links":{"citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:17a1841904baa867e95d764a375e68917781ec6f2e2100ab55ccd4ca662b3837","observation_id":"daac7867-7860-4232-906f-d8f9a0e09b22","resolution":{"observed_at":"2026-08-07T05:36:58.590629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-07T05:36:58.179549Z","title":"𝑏𝑖𝑟𝑑\" \"𝑑𝑜𝑔","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:58.179549Z"},"links":{"cited_paper":"/paper/2307.15043","citing_paper":"/paper/2506.07596"},"observation_digest":"sha256:de38add25c9e4fbf4b103bc9a87d424497ef22fa0ef0830810ece34b2734db01","observation_id":"cf19b872-e853-43ed-807b-73791d8b8c34","resolution":{"observed_at":"2026-08-07T05:36:58.179549Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.07596","last_updated":"2025-06-09T09:54:25Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T08:29:55.291442Z","submitted_at":"2025-06-09T09:54:25Z","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts"},"reference_resolution":{"displayed":75,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":30,"verified_exact":0,"verified_fuzzy":42},"total_outbound_references":75},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2506.07596."}