{"as_of":"2026-08-07T18:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1fbd531395b43a73a4f18b2f0b98aadb6dd2e456c852650348a9b2f628ed789d","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:00:19.643921Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T08:45:52.855783Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-15T02:13:30.051815Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"cited_work":{"arxiv_id":"2506.20251","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20251","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2506.20251 , year=","venue":null,"work_id":"20b23add-6f0f-4e0c-b237-768ce98c4205","year":null},"citing_paper":{"arxiv_id":"2605.14404","last_updated":"2026-05-14T05:45:24Z","snapshot_observed_at":"2026-07-06T23:25:49.545418Z","submitted_at":"2026-05-14T05:45:24Z","title":"Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-05-15T02:13:17.039114Z"},"links":{"cited_paper":"/paper/2506.20251","citing_paper":"/paper/2605.14404"},"observation_digest":"sha256:a5e278b9de1c374838a5d9796974f07bb6d1a106b630c8f40bc1a56244302724","observation_id":"1a36ddfb-7141-4243-95c9-f0d1c6cd1d7f","resolution":{"observed_at":"2026-05-15T02:13:30.053304Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20251","snapshot_observed_at":"2026-07-14T08:45:52.855783Z","title":"arXiv preprint arXiv:2506.20251 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10855","last_updated":"2026-07-12T17:39:09Z","snapshot_observed_at":"2026-08-06T03:10:18.618115Z","submitted_at":"2026-07-12T17:39:09Z","title":"Reliability Scaling Laws for Quantized Large Language Models","version":1},"reference_index":148,"source":"arxiv_source","source_observed_at":"2026-07-14T08:45:52.855783Z"},"links":{"cited_paper":"/paper/2506.20251","citing_paper":"/paper/2607.10855"},"observation_digest":"sha256:85c9fabf049abf95ac9ddbe68849e991f6ac93b2345b8a6294b9f05f093e1ef2","observation_id":"49685228-f86e-4eb3-901e-86c011bb2c24","resolution":{"observed_at":"2026-07-14T08:45:52.855783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.20251/citation-record","integrity":"/paper/2506.20251/integrity","json":"/paper/2506.20251/citation-record.json","paper":"/paper/2506.20251"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.00456","last_updated":"2024-10-29T11:09:12Z","snapshot_observed_at":"2026-08-05T10:45:45.389337Z","submitted_at":"2024-03-30T19:20:06Z","title":"QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.00456","snapshot_observed_at":"2026-08-06T23:00:19.487900Z","title":"L., Li, B., Jaggi, M., Alistarh, D., Hoefler, T., and Hensman, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.487900Z"},"links":{"cited_paper":"/paper/2404.00456","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:205fc9b6a46c334c7bd4335c4ca475d7009ac213309c99208afce2a4a15b02e0","observation_id":"5e0785be-b6c2-490b-8182-a791103ad961","resolution":{"observed_at":"2026-08-06T23:00:19.487900Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.03146","last_updated":"2024-05-08T02:10:36Z","snapshot_observed_at":"2026-07-06T18:10:12.621492Z","submitted_at":"2024-05-06T03:42:34Z","title":"Quantifying the Capabilities of LLMs across Scale and Precision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.03146","snapshot_observed_at":"2026-08-06T23:00:19.492020Z","title":"and Sajjad, H","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.492020Z"},"links":{"cited_paper":"/paper/2405.03146","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:f396a9c891ab4ecc2195508176e686ec43c6319a28c2dcbeb3a8f8410f6ae9b2","observation_id":"4539ba0d-6f7a-472c-a27c-c1b85ec456a7","resolution":{"observed_at":"2026-08-06T23:00:19.492020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-06T23:00:19.495735Z","title":"Training a helpful and harmless assistant with rein- forcement learning from human feedback.arXiv preprint arXiv:2204.05862,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.495735Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:719cc773fcf743843a4944ed392177683d8683935253aef4726213db9a4e99fe","observation_id":"00875733-8dc6-4479-b87f-39693db4771b","resolution":{"observed_at":"2026-08-06T23:00:19.495735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.08162","last_updated":"2023-06-13T22:25:35Z","snapshot_observed_at":"2026-07-06T15:42:18.360486Z","submitted_at":"2023-06-13T22:25:35Z","title":"INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.08162","snapshot_observed_at":"2026-08-06T23:00:19.503155Z","title":"G., Brooks, D., and Wei, G.-Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.503155Z"},"links":{"cited_paper":"/paper/2306.08162","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:97e7acf0781c907f62214bb74a508fd9f2422af85e9a88aabd4b81a8752306e4","observation_id":"d9fbfd4e-e824-401d-b391-772d2b489a83","resolution":{"observed_at":"2026-08-06T23:00:19.503155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.10683","last_updated":"2022-10-19T15:53:36Z","snapshot_observed_at":"2026-08-06T03:33:05.031960Z","submitted_at":"2022-10-19T15:53:36Z","title":"Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.10683","snapshot_observed_at":"2026-08-06T23:00:19.506346Z","title":"Why should adversarial perturbations be imper- ceptible? rethink the research paradigm in adversarial nlp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.506346Z"},"links":{"cited_paper":"/paper/2210.10683","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:eb54070c81ac56ad88fdf26ccc96ac88d7b48535d7824c295b49200987eb06d6","observation_id":"fbfdd1f4-5006-4668-ad4d-d7defadad16f","resolution":{"observed_at":"2026-08-06T23:00:19.506346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10944","last_updated":"2023-10-17T02:42:34Z","snapshot_observed_at":"2026-07-06T16:34:15.491281Z","submitted_at":"2023-10-17T02:42:34Z","title":"TEQ: Trainable Equivalent Transformation for Quantization of LLMs","version":1},"cited_work":{"arxiv_id":"2310.10944","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.10944","snapshot_observed_at":"2026-08-06T23:00:19.961004Z","title":"TEQ: Trainable Equivalent Transformation for Quantization of LLMs","venue":"cs.CL","work_id":"819b9e55-bbeb-47f9-8257-483ffca340f2","year":2023},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.509727Z"},"links":{"cited_paper":"/paper/2310.10944","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:cdea1e559c1035f54cefca55c07f2a148dd8f1fe09700b592e65b8af14643128","observation_id":"689babd4-9ad4-4521-843a-937a500f0bd1","resolution":{"observed_at":"2026-08-06T23:00:19.965307Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01377","last_updated":"2024-07-16T03:24:39Z","snapshot_observed_at":"2026-08-02T07:46:40.319683Z","submitted_at":"2023-10-02T17:40:01Z","title":"UltraFeedback: Boosting Language Models with Scaled AI Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01377","snapshot_observed_at":"2026-08-06T23:00:19.516351Z","title":"Ultrafeedback: Boosting lan- guage models with high-quality feedback.arXiv preprint arXiv:2310.01377,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.516351Z"},"links":{"cited_paper":"/paper/2310.01377","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:66c7bb62f350c03173281dfe63fb52ba474f521d0bfb34ae8b4e96cb004b267a","observation_id":"d33b3879-494b-40f1-a65a-20f6c9abcd64","resolution":{"observed_at":"2026-08-06T23:00:19.516351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03078","last_updated":"2023-06-05T17:53:28Z","snapshot_observed_at":"2026-08-07T09:56:21.569200Z","submitted_at":"2023-06-05T17:53:28Z","title":"SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03078","snapshot_observed_at":"2026-08-06T23:00:19.519528Z","title":"Spqr: A sparse-quantized representation for near-lossless llm weight compression.arXiv preprint arXiv:2306.03078,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.519528Z"},"links":{"cited_paper":"/paper/2306.03078","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:f7f3bd0023796a0746a52bd733099d76ff84ad3acd82410511df95f874f7edd2","observation_id":"9eda0494-dd20-4f21-be98-f0f98ace6a74","resolution":{"observed_at":"2026-08-06T23:00:19.519528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14233","last_updated":"2023-05-23T16:49:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-23T16:49:14Z","title":"Enhancing Chat Language Models by Scaling High-quality Instructional Conversations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14233","snapshot_observed_at":"2026-08-06T23:00:19.522619Z","title":"Enhancing chat language mod- els by scaling high-quality instructional conversations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.522619Z"},"links":{"cited_paper":"/paper/2305.14233","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:5f3b3cd5c2d1833f497c40eeb718d6128ec08bbb619daf614c6500a08aabfcc2","observation_id":"8ad88c67-5de8-455f-90cc-bd4460508410","resolution":{"observed_at":"2026-08-06T23:00:19.522619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10631","last_updated":"2024-02-16T12:27:15Z","snapshot_observed_at":"2026-07-06T17:31:08.762955Z","submitted_at":"2024-02-16T12:27:15Z","title":"BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10631","snapshot_observed_at":"2026-08-06T23:00:19.525721Z","title":"Bitdistiller: Unleashing the potential of sub-4-bit llms via self-distillation.arXiv preprint arXiv:2402.10631,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.525721Z"},"links":{"cited_paper":"/paper/2402.10631","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:c4876106ca553df6903800387405a3778ecaf9690916073a9d35cc18c9a75aeb","observation_id":"1ae8183d-82e0-46cc-9bf1-0bb9076891e9","resolution":{"observed_at":"2026-08-06T23:00:19.525721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18137","last_updated":"2024-11-04T11:16:38Z","snapshot_observed_at":"2026-07-06T18:21:18.150567Z","submitted_at":"2024-05-28T12:51:01Z","title":"Exploiting LLM Quantization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18137","snapshot_observed_at":"2026-08-06T23:00:19.528854Z","title":"Exploiting llm quantization.arXiv preprint arXiv:2405.18137,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.528854Z"},"links":{"cited_paper":"/paper/2405.18137","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:adc79afb50ee42384e6199d524faa62e56b6c878b951814d5fa31c96dbd6be6d","observation_id":"64ba23fe-bd76-43e3-8320-52f2e528e5f8","resolution":{"observed_at":"2026-08-06T23:00:19.528854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.06118","last_updated":"2024-09-11T07:48:26Z","snapshot_observed_at":"2026-08-06T11:31:16.355778Z","submitted_at":"2024-01-11T18:54:44Z","title":"Extreme Compression of Large Language Models via Additive Quantization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.06118","snapshot_observed_at":"2026-08-06T23:00:19.532049Z","title":"Extreme compression of large language models via additive quantization.arXiv preprint arXiv:2401.06118,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.532049Z"},"links":{"cited_paper":"/paper/2401.06118","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:d5eabc2c9bc1a5cf317786546b9083c20394dc5250fee27dfc3393a843c8f980","observation_id":"58eaad20-086d-4325-9ae9-7323145700c7","resolution":{"observed_at":"2026-08-06T23:00:19.532049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.17323","last_updated":"2023-03-22T13:10:47Z","snapshot_observed_at":"2026-08-07T08:38:54.025062Z","submitted_at":"2022-10-31T13:42:40Z","title":"GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.17323","snapshot_observed_at":"2026-08-06T23:00:19.539701Z","title":"Gptq: Accurate post-training quantization for generative pre- trained transformers.arXiv preprint arXiv:2210.17323,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.539701Z"},"links":{"cited_paper":"/paper/2210.17323","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:64442320f363acfa50a19e96581da2292694f0dce1c50a6e5912725b1c4aff2f","observation_id":"3340f34a-0738-4f92-a433-a33eb67a963e","resolution":{"observed_at":"2026-08-06T23:00:19.539701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12023","last_updated":"2024-08-27T00:48:35Z","snapshot_observed_at":"2026-07-06T16:50:06.095609Z","submitted_at":"2023-11-20T18:57:41Z","title":"LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12023","snapshot_observed_at":"2026-08-06T23:00:19.542797Z","title":"P., and Kim, Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.542797Z"},"links":{"cited_paper":"/paper/2311.12023","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:c295067e0791854c29cbd69400e8fe15555294baaac0677ef66b86efa7f85219","observation_id":"60016d0c-8bf3-48c2-b1e7-caa4e00fe9b7","resolution":{"observed_at":"2026-08-06T23:00:19.542797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12354","last_updated":"2024-07-04T18:33:00Z","snapshot_observed_at":"2026-08-03T17:12:16.534784Z","submitted_at":"2024-02-19T18:33:49Z","title":"LoRA+: Efficient Low Rank Adaptation of Large Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12354","snapshot_observed_at":"2026-08-06T23:00:19.546271Z","title":"Lora+: Efficient low rank adaptation of large models.arXiv preprint arXiv:2402.12354,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.546271Z"},"links":{"cited_paper":"/paper/2402.12354","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:6fa4fd7c647b6a3a430972509c0980234aa0cc4ff5658579d7f2dbc65859bb30","observation_id":"716ca101-91a8-4787-99ac-ca851702663f","resolution":{"observed_at":"2026-08-06T23:00:19.546271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.19883","last_updated":"2024-07-20T06:00:22Z","snapshot_observed_at":"2026-07-06T18:22:36.012485Z","submitted_at":"2024-05-30T09:42:54Z","title":"From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems","version":2},"cited_work":{"arxiv_id":"2405.19883","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.19883","snapshot_observed_at":"2026-08-06T23:00:19.867380Z","title":"From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems","venue":"cs.LG","work_id":"b7abdf48-0daa-4a8e-aa80-6a42b44c0cbb","year":2024},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.549520Z"},"links":{"cited_paper":"/paper/2405.19883","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:8272010680a3a21b9a3c6faa613803869a7ed1134880d3bddd127e593f8fa943","observation_id":"0ca9828c-5f3b-459c-9652-10c4bb43c315","resolution":{"observed_at":"2026-08-06T23:00:19.872934Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.15447","last_updated":"2024-06-04T05:40:12Z","snapshot_observed_at":"2026-07-06T17:49:11.762370Z","submitted_at":"2024-03-18T01:38:19Z","title":"Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.15447","snapshot_observed_at":"2026-08-06T23:00:19.552626Z","title":"Decoding compressed trust: Scrutinizing the trust- worthiness of efficient llms under compression.arXiv preprint arXiv:2403.15447,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.552626Z"},"links":{"cited_paper":"/paper/2403.15447","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:182e7b0e66d103394546b6d589059a7f5fffce2bac1589984dfe80ee2ac14904","observation_id":"56b4a5db-6959-4436-9fa4-fb83cdcf6016","resolution":{"observed_at":"2026-08-06T23:00:19.552626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06987","last_updated":"2023-10-10T20:15:54Z","snapshot_observed_at":"2026-07-06T16:30:46.321160Z","submitted_at":"2023-10-10T20:15:54Z","title":"Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06987","snapshot_observed_at":"2026-08-06T23:00:19.555633Z","title":"Catas- trophic jailbreak of open-source llms via exploiting gen- eration.arXiv preprint arXiv:2310.06987,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.555633Z"},"links":{"cited_paper":"/paper/2310.06987","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:527152127ff3253d7b17b51e54f6d59a308178dc789177d3d1dc6b05b120fcfb","observation_id":"4e63ccb5-8ef6-4bcf-a40c-d785d3254895","resolution":{"observed_at":"2026-08-06T23:00:19.555633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.07629","last_updated":"2024-06-05T03:57:41Z","snapshot_observed_at":"2026-08-05T21:17:46.828705Z","submitted_at":"2023-06-13T08:57:54Z","title":"SqueezeLLM: Dense-and-Sparse Quantization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.07629","snapshot_observed_at":"2026-08-06T23:00:19.558832Z","title":"H., Kim, S., Park, J., Yoo, K","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.558832Z"},"links":{"cited_paper":"/paper/2306.07629","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:018205fb89970c2f4a4726d0fbfa05946ef46a53dae00eaa4ee71394dc4867e6","observation_id":"53dfb406-e291-4a4b-badf-f4e1a106241a","resolution":{"observed_at":"2026-08-06T23:00:19.558832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10076","last_updated":"2024-02-15T16:38:41Z","snapshot_observed_at":"2026-08-07T09:28:54.765101Z","submitted_at":"2024-02-15T16:38:41Z","title":"QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10076","snapshot_observed_at":"2026-08-06T23:00:19.562688Z","title":"Quick: Quantization-aware interleaving and conflict-free kernel for efficient llm inference.arXiv preprint arXiv:2402.10076, 2024b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.562688Z"},"links":{"cited_paper":"/paper/2402.10076","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:70b1761cb98ff456c6b553a5b33ac8f894407ffa189cd99f493bc9cb0acf8dd2","observation_id":"e85c48a5-6869-4fa6-a91f-b814b854d16e","resolution":{"observed_at":"2026-08-06T23:00:19.562688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08041","last_updated":"2024-04-06T10:22:57Z","snapshot_observed_at":"2026-08-03T13:48:04.987290Z","submitted_at":"2023-10-12T05:25:49Z","title":"QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08041","snapshot_observed_at":"2026-08-06T23:00:19.569973Z","title":"Awq: Activation-aware weight quantization for on-device llm compression and acceleration.Proceedings of Machine Learning and Systems, 6:87–100, 2024b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.569973Z"},"links":{"cited_paper":"/paper/2310.08041","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:52549038caf4c584c89c890e1a9165be59862a2c41ad769b49d6bbac908c98c1","observation_id":"d6ce4aef-7da2-4931-a3a7-8f5f2d8ea19b","resolution":{"observed_at":"2026-08-06T23:00:19.569973Z","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":"2026-08-06T23:00:19.573170Z","title":"Harm- bench: A standardized evaluation framework for auto- mated red teaming and robust refusal.arXiv preprint arXiv:2402.04249,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.573170Z"},"links":{"cited_paper":"/paper/2402.04249","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:f6e5c23a2c584f0fbcf802d8b9862d21846a24cf5bbecae5378af42c3648b762","observation_id":"7581cd33-ceb0-42cc-8e90-1deb6d8272e1","resolution":{"observed_at":"2026-08-06T23:00:19.573170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.20835","last_updated":"2024-06-05T09:53:18Z","snapshot_observed_at":"2026-07-06T18:23:19.450809Z","submitted_at":"2024-05-31T14:24:33Z","title":"Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.20835","snapshot_observed_at":"2026-08-06T23:00:19.576498Z","title":"Outliers and calibration sets have diminishing ef- fect on quantization of modern llms.arXiv preprint arXiv:2405.20835,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.576498Z"},"links":{"cited_paper":"/paper/2405.20835","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:c6b2811c4178df7b34e12e6d140f40667fd7977883450472d5e8ebbf11c50333","observation_id":"a274cb67-87a7-462f-9018-4af02697adeb","resolution":{"observed_at":"2026-08-06T23:00:19.576498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03693","last_updated":"2023-10-05T17:12:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-05T17:12:17Z","title":"Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03693","snapshot_observed_at":"2026-08-06T23:00:19.583683Z","title":"Fine-tuning aligned language models compromises safety, even when users do not intend to! arXiv preprint arXiv:2310.03693,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.583683Z"},"links":{"cited_paper":"/paper/2310.03693","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:ddd5d4234cfe26ee33c9123b8f13a089114c19dcab319bb12bba3b77a575b11a","observation_id":"9d15065a-dc73-4f80-8dce-f8478c36e740","resolution":{"observed_at":"2026-08-06T23:00:19.583683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01964","last_updated":"2024-06-17T12:48:46Z","snapshot_observed_at":"2026-07-06T18:09:17.538646Z","submitted_at":"2024-05-03T09:41:39Z","title":"Position: Understanding LLMs Requires More Than Statistical Generalization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01964","snapshot_observed_at":"2026-08-06T23:00:19.586821Z","title":"Understanding llms requires more than statistical generalization.arXiv preprint arXiv:2405.01964,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.586821Z"},"links":{"cited_paper":"/paper/2405.01964","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:f9eca87a63b8a7a81dd86495464a8da0b4625215dc2aed3651f8933b77333aca","observation_id":"6d222a10-dc3c-43b4-a92f-a14a9784836f","resolution":{"observed_at":"2026-08-06T23:00:19.586821Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00034","last_updated":"2023-11-07T20:41:22Z","snapshot_observed_at":"2026-07-06T16:25:42.545425Z","submitted_at":"2023-09-29T14:35:27Z","title":"PB-LLM: Partially Binarized Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00034","snapshot_observed_at":"2026-08-06T23:00:19.590254Z","title":"Pb-llm: Par- tially binarized large language models.arXiv preprint arXiv:2310.00034,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.590254Z"},"links":{"cited_paper":"/paper/2310.00034","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:2992e5cdbf97fc2c3b8d5b4461f7be9205406ce7985e389f64ba14f4f8a5cfa8","observation_id":"0996d68a-fd79-417b-a84d-e650e408bd8b","resolution":{"observed_at":"2026-08-06T23:00:19.590254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.13137","last_updated":"2024-03-18T05:33:22Z","snapshot_observed_at":"2026-07-06T16:10:15.694898Z","submitted_at":"2023-08-25T02:28:35Z","title":"OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.13137","snapshot_observed_at":"2026-08-06T23:00:19.593559Z","title":"Omniquant: Omnidirectionally calibrated quantization for large lan- guage models.arXiv preprint arXiv:2308.13137,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.593559Z"},"links":{"cited_paper":"/paper/2308.13137","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:a3028305dbc0405c4fe6e8d74aac148c35b23c74c9d2e1ad09b9c3a7c6f7e810","observation_id":"39d67b9d-8413-474a-82c7-dcfcc9e8db8e","resolution":{"observed_at":"2026-08-06T23:00:19.593559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10260","last_updated":"2024-08-27T03:32:47Z","snapshot_observed_at":"2026-08-04T21:32:35.483431Z","submitted_at":"2024-02-15T18:58:09Z","title":"A StrongREJECT for Empty Jailbreaks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10260","snapshot_observed_at":"2026-08-06T23:00:19.597335Z","title":"A strongreject for empty jailbreaks.arXiv preprint arXiv:2402.10260,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.597335Z"},"links":{"cited_paper":"/paper/2402.10260","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:3ce15dfea974baa50a9b99ed32a972388996612b9fa2e5f9359d10c63de262ee","observation_id":"9349d506-9723-4722-8c1d-6ac5b156a399","resolution":{"observed_at":"2026-08-06T23:00:19.597335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-06T23:00:19.601286Z","title":"G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahri- ari, B., Ram ´e, A., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.601286Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:fc0a127deb720e8015ab18877ad7fec9d475e7ebdd1f9d37f8dc1f2c5471f028","observation_id":"498f0760-32de-46d1-ad71-287ca6a6e97c","resolution":{"observed_at":"2026-08-06T23:00:19.601286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-06T23:00:19.604475Z","title":"Llama 2: Open foundation and fine- tuned chat models.arXiv preprint arXiv:2307.09288,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.604475Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:e15679bd6f8501abaf12a3ed78cf7b682f751692a6fa25dc3589c27398f4f416","observation_id":"bfd6f8d0-9bf1-40e0-93b6-c105454220da","resolution":{"observed_at":"2026-08-06T23:00:19.604475Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.16944","last_updated":"2023-10-25T19:25:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-25T19:25:16Z","title":"Zephyr: Direct Distillation of LM Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.16944","snapshot_observed_at":"2026-08-06T23:00:19.607683Z","title":"Zephyr: Direct distillation of lm alignment.arXiv preprint arXiv:2310.16944,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.607683Z"},"links":{"cited_paper":"/paper/2310.16944","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:671bebdf5b0b2a05ddc4fc4372ebb97466afdc672b1f3972660458b1b0a20b62","observation_id":"9b293a47-23d1-4807-8d7a-b34cb4df8079","resolution":{"observed_at":"2026-08-06T23:00:19.607683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.09145","last_updated":"2023-10-23T08:48:31Z","snapshot_observed_at":"2026-07-06T15:17:05.623407Z","submitted_at":"2023-04-18T17:34:23Z","title":"Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.09145","snapshot_observed_at":"2026-08-06T23:00:19.611331Z","title":"Outlier suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling.arXiv preprint arXiv:2304.09145,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.611331Z"},"links":{"cited_paper":"/paper/2304.09145","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:7967b96115454f4a4842363efecc0979325720d63f10d71954aa522692eb6b48","observation_id":"32bf6349-d0e6-4e50-bce4-50b815969fc6","resolution":{"observed_at":"2026-08-06T23:00:19.611331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03771","last_updated":"2020-07-14T03:42:34Z","snapshot_observed_at":"2026-07-06T08:27:58.343233Z","submitted_at":"2019-10-09T03:23:22Z","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03771","snapshot_observed_at":"2026-08-06T23:00:19.614654Z","title":"Transformers: State-of-the-art natural language processing.arXiv preprint arXiv:1910.03771,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.614654Z"},"links":{"cited_paper":"/paper/1910.03771","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:b481d562f8cb55cdcad75dd0ebdf358ace78f4aa3f765d36c48d26a3cd4c15d6","observation_id":"d1466df5-fb21-4e86-879e-5d9ad4bd481f","resolution":{"observed_at":"2026-08-06T23:00:19.614654Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.14717","last_updated":"2023-10-09T07:39:04Z","snapshot_observed_at":"2026-08-03T21:40:53.000035Z","submitted_at":"2023-09-26T07:22:23Z","title":"QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.14717","snapshot_observed_at":"2026-08-06T23:00:19.617930Z","title":"Qa-lora: Quantization- aware low-rank adaptation of large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.617930Z"},"links":{"cited_paper":"/paper/2309.14717","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:df4d52bc661baa5bbe2ab6ac77e81925eb5c0822ab252356667f03df425952b5","observation_id":"56838325-0136-47d9-a8c0-582bab515fe5","resolution":{"observed_at":"2026-08-06T23:00:19.617930Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11295","last_updated":"2024-11-29T11:47:55Z","snapshot_observed_at":"2026-07-06T17:31:37.574049Z","submitted_at":"2024-02-17T14:26:57Z","title":"OneBit: Towards Extremely Low-bit Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11295","snapshot_observed_at":"2026-08-06T23:00:19.621017Z","title":"Onebit: Towards extremely low-bit large language models.arXiv preprint arXiv:2402.11295, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.621017Z"},"links":{"cited_paper":"/paper/2402.11295","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:08bd718f30b43e4b74653baf5b6ab1895ce1a2ff4ed8f6c6075d20da667efd97","observation_id":"401a0149-7bef-4eb7-95a5-cff96ea5e6e1","resolution":{"observed_at":"2026-08-06T23:00:19.621017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.01089","last_updated":"2023-05-17T10:07:33Z","snapshot_observed_at":"2026-07-06T15:11:32.429514Z","submitted_at":"2023-04-03T15:46:15Z","title":"RPTQ: Reorder-based Post-training Quantization for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.01089","snapshot_observed_at":"2026-08-06T23:00:19.624008Z","title":"Rptq: Reorder-based post- training quantization for large language models.arXiv preprint arXiv:2304.01089,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.624008Z"},"links":{"cited_paper":"/paper/2304.01089","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:70174693c71262626c5e5cbdab1b955d3433f5d7732f0a4640fda9386524f51d","observation_id":"3c95b49e-d931-464c-98ec-bb89f3495c16","resolution":{"observed_at":"2026-08-06T23:00:19.624008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17436","last_updated":"2024-08-05T18:12:27Z","snapshot_observed_at":"2026-08-06T17:34:58.933900Z","submitted_at":"2024-07-11T21:16:48Z","title":"AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.17436","snapshot_observed_at":"2026-08-06T23:00:19.627162Z","title":"Z., Tu, Y ., Mai, Y ., Kly- man, K., Pan, M., Jia, R., Song, D., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.627162Z"},"links":{"cited_paper":"/paper/2407.17436","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:72b5e5cac432493e7c7a7c81527e750137c9b195b535318bb20e6ed60b2351a2","observation_id":"0f2d9e24-efd8-43c9-bf37-44c75b1e2e61","resolution":{"observed_at":"2026-08-06T23:00:19.627162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.00840","last_updated":"2025-06-10T17:24:15Z","snapshot_observed_at":"2026-08-06T21:20:37.114337Z","submitted_at":"2025-02-02T16:25:48Z","title":"Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.00840","snapshot_observed_at":"2026-08-06T23:00:19.630547Z","title":"Activation approxima- tions can incur safety vulnerabilities even in aligned llms: Comprehensive analysis and defense.arXiv preprint arXiv:2502.00840,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.630547Z"},"links":{"cited_paper":"/paper/2502.00840","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:7c08ef6ff7c82f1d51209e2e01702e19159b2961f83cf76d6694d5c4f94eb78a","observation_id":"80a66c5d-3841-47f2-9391-cd8c2d36cf8c","resolution":{"observed_at":"2026-08-06T23:00:19.630547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.15043","last_updated":"2023-12-20T20:48:57Z","snapshot_observed_at":"2026-07-06T15:59:23.019044Z","submitted_at":"2023-07-27T17:49:12Z","title":"Universal and Transferable Adversarial Attacks on Aligned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15043","snapshot_observed_at":"2026-08-06T23:00:19.633676Z","title":"Z., and Fredrikson, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.633676Z"},"links":{"cited_paper":"/paper/2307.15043","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:5942bf772e39bb1f3822f0799683a930b4a747c32f6ccb744ce92d6e2b7280b5","observation_id":"0365a828-9cb1-4377-b751-7c28b563deeb","resolution":{"observed_at":"2026-08-06T23:00:19.633676Z","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":"2026-08-06T23:00:20.056407Z","title":null,"venue":null,"work_id":"4cff80df-c01c-416f-857c-79bb5a096a9a","year":2024},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.637507Z"},"links":{"citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:8ca3df014949255f39f6b7244d90f45e51cf6c6d7915739523416be939f3645a","observation_id":"45ed98f6-7de5-4da7-a5fd-2cee95970f5f","resolution":{"observed_at":"2026-08-06T23:00:20.059874Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:00:20.047689Z","title":"ASRVanilla: Tested with system prompt:”You are a helpful assistant","venue":null,"work_id":"2c41df61-aadf-48ed-9706-456ad1b2cb92","year":2024},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.640521Z"},"links":{"citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:8a5492b997ae3dfa0847e5fb7d21f2cf34c847eae147429705d0308cf55cd242","observation_id":"db635d82-38aa-4af0-8cb0-13afb93fa4db","resolution":{"observed_at":"2026-08-06T23:00:20.050712Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:00:20.037678Z","title":null,"venue":null,"work_id":"e686e4ff-1002-4817-81bc-7605b5f66580","year":2023},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.643921Z"},"links":{"citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:6fe14fb1068a7eace0b479465bd83cb1c8bfadf0c4adc1bd5f91dc595b9ae86a","observation_id":"6a5ff4c0-fa57-478d-b2a6-dde65acec5ab","resolution":{"observed_at":"2026-08-06T23:00:20.040409Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05668","last_updated":"2025-05-26T12:56:04Z","snapshot_observed_at":"2026-07-06T17:27:24.955378Z","submitted_at":"2024-02-08T13:42:50Z","title":"JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05668","snapshot_observed_at":"2026-08-06T23:00:19.513275Z","title":"Comprehensive assessment of jailbreak attacks against llms.arXiv preprint arXiv:2402.05668,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.513275Z"},"links":{"cited_paper":"/paper/2402.05668","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:160e1d28ae5ee178e3b7a9ddbccf0b3afa25bcca999af1d8760efedfada56767","observation_id":"53031d22-f6a6-49d8-938f-7cc3cf6f8c47","resolution":{"observed_at":"2026-08-06T23:00:19.513275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05044","last_updated":"2024-06-07T12:05:46Z","snapshot_observed_at":"2026-08-03T21:40:53.683032Z","submitted_at":"2024-02-07T17:33:54Z","title":"SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05044","snapshot_observed_at":"2026-08-06T23:00:19.566396Z","title":"Salad-bench: A hierarchical and com- prehensive safety benchmark for large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.566396Z"},"links":{"cited_paper":"/paper/2402.05044","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:d6c2e1d5c6ca732a8a132dd9f59d3f35c123b09b63e1bf050aff45a1db00b005","observation_id":"7a90c41f-4898-42d3-86d6-c6a44e90120a","resolution":{"observed_at":"2026-08-06T23:00:19.566396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03277","last_updated":"2023-04-06T17:58:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-06T17:58:09Z","title":"Instruction Tuning with GPT-4","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03277","snapshot_observed_at":"2026-08-06T23:00:19.579669Z","title":"Instruc- tion tuning with gpt-4.arXiv preprint arXiv:2304.03277,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.579669Z"},"links":{"cited_paper":"/paper/2304.03277","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:555e98c25731cec70d9b9dc1bc82c07ce543533d568051584ca8d32a5f7928cd","observation_id":"c5b92e23-f8ed-45b8-bf7e-95e66bc372b8","resolution":{"observed_at":"2026-08-06T23:00:19.579669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.06835","last_updated":"2024-11-11T10:02:49Z","snapshot_observed_at":"2026-08-06T17:49:16.607960Z","submitted_at":"2024-11-11T10:02:49Z","title":"HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.06835","snapshot_observed_at":"2026-08-06T23:00:19.499755Z","title":"Harmlevel- bench: Evaluating harm-level compliance and the im- pact of quantization on model alignment.arXiv preprint arXiv:2411.06835,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.499755Z"},"links":{"cited_paper":"/paper/2411.06835","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:6d36d922a6f4b15e3963ece1ed6ed1eeaaf518cb0fc282c336c257e475c1b879","observation_id":"b4a0c716-2058-454d-83ed-a637157748f5","resolution":{"observed_at":"2026-08-06T23:00:19.499755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T23:00:19.480415Z","title":"L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.480415Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:f05a3f6f575cb8f1eedb09c9898063439f733c54863719793269cf0ad42f2452","observation_id":"f7021a1b-5078-4ed8-8cf5-53e483c72be2","resolution":{"observed_at":"2026-08-06T23:00:19.480415Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10403","last_updated":"2023-09-13T20:35:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T17:46:53Z","title":"PaLM 2 Technical Report","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10403","snapshot_observed_at":"2026-08-06T23:00:19.484466Z","title":"M., Firat, O., Johnson, M., Lepikhin, D., Passos, A., Shakeri, S., Taropa, E., Bailey, P., Chen, Z., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.484466Z"},"links":{"cited_paper":"/paper/2305.10403","citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:90efff08ab05fb0553a72db52627190c2134f4de87ba398961df904b3a52a223","observation_id":"5341d5a9-ed0c-4624-8130-c5348f4c79a9","resolution":{"observed_at":"2026-08-06T23:00:19.484466Z","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":"2026-08-06T23:00:20.067560Z","title":"Accessed: 2025-01-24","venue":null,"work_id":"c099aba4-286f-4488-8a7f-6354566cd2d5","year":2025},"citing_paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T23:00:19.535729Z"},"links":{"citing_paper":"/paper/2506.20251"},"observation_digest":"sha256:2af2bc8b46e61d74b6d0c872ce0ec95886851a95974c7213cfe9fd42a7b6ef7c","observation_id":"730be733-a0db-446d-babf-ddc3c399ef90","resolution":{"observed_at":"2026-08-06T23:00:20.071040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.20251","last_updated":"2025-06-25T08:52:22Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T18:04:53.832466Z","submitted_at":"2025-06-25T08:52:22Z","title":"Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":45,"verified_exact":2,"verified_fuzzy":1},"total_outbound_references":49},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 inbound Pith citation observations for arXiv:2506.20251."}