{"as_of":"2026-08-10T15:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d9f5ac657967d405d1df796212c64418f0437ef46789846ee7f0b28b3fd37724","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T14:50:31.100765Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2509.23381/citation-record","integrity":"/paper/2509.23381/integrity","json":"/paper/2509.23381/citation-record.json","paper":"/paper/2509.23381"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.938465Z","title":"Llm-jp toxicity dataset v2","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.938465Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:1e4b56bf03c1690e708fa251693fb251ddb0e9dd741d885985b4a9e11bb5e910","observation_id":"202bb892-4046-4c0b-908d-5be0c01b09b9","resolution":{"observed_at":"2026-08-04T14:50:30.938465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.08073","last_updated":"2022-12-15T06:19:23Z","snapshot_observed_at":"2026-08-02T04:53:58.766070Z","submitted_at":"2022-12-15T06:19:23Z","title":"Constitutional AI: Harmlessness from AI Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.08073","snapshot_observed_at":"2026-08-04T14:50:30.942099Z","title":"Constitutional ai: Harmlessness from ai feedback","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.942099Z"},"links":{"cited_paper":"/paper/2212.08073","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:2481eb960eb1a102f6a886f555558d7f62c6b7088f5cb4295c3affb30a8699fd","observation_id":"353c4e7b-4480-4596-8a00-3e4554d4d61d","resolution":{"observed_at":"2026-08-04T14:50:30.942099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.04672","last_updated":"2022-08-25T17:10:53Z","snapshot_observed_at":"2026-07-06T13:29:47.927628Z","submitted_at":"2022-07-11T07:33:36Z","title":"No Language Left Behind: Scaling Human-Centered Machine Translation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.04672","snapshot_observed_at":"2026-08-04T14:50:30.946190Z","title":"No language left behind: Scaling human-centered machine translation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.946190Z"},"links":{"cited_paper":"/paper/2207.04672","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:7b1a73d489937ec7682256553f519c3c0473d22b8b66408243f1689da646fb2d","observation_id":"f45b1755-3e9d-445a-98b7-49a0a2569c51","resolution":{"observed_at":"2026-08-04T14:50:30.946190Z","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":"2026-08-04T14:50:30.949543Z","title":"Gptq: Accurate post-training quantization for generative pre-trained transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.949543Z"},"links":{"cited_paper":"/paper/2210.17323","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:0d9f098ebdf9327b0b302ce561a6781c51ddae95923050aec6c0765d3295efa0","observation_id":"014a138d-d8ed-4994-9d13-bf7bdb5a943e","resolution":{"observed_at":"2026-08-04T14:50:30.949543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.952885Z","title":"Continual pre-training for cross-lingual llm adaptation: Enhancing japanese language capabilities","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.952885Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:4ee097cdb46e27684bdbd52b2da361112d7930571aaa22445cbd5e7a36a0fbe1","observation_id":"9620af36-9ec1-4310-ba64-0385615d9cb4","resolution":{"observed_at":"2026-08-04T14:50:30.952885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.956154Z","title":"AEGIS 2.0: A diverse AI safety dataset and risks taxonomy for alignment of LLM guardrails","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.956154Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:182d908b2b5c53ec1a11f1bae4d02626c641caf01396a8f968ef2acbdb9ca0e2","observation_id":"ff26142c-c0cd-4d8e-87a8-0add72fa0375","resolution":{"observed_at":"2026-08-04T14:50:30.956154Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16137","last_updated":"2024-06-24T21:22:00Z","snapshot_observed_at":"2026-08-10T13:57:06.597469Z","submitted_at":"2023-08-30T16:47:51Z","title":"LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16137","snapshot_observed_at":"2026-08-04T14:50:30.959453Z","title":"Lm-infinite: Zero-shot extreme length generalization for large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.959453Z"},"links":{"cited_paper":"/paper/2308.16137","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:5ba81955b2708afeae07e9e7e7508ba493a595b2083f958d67add2eee8073eec","observation_id":"aea2deaf-e721-4bce-ae6b-4597daea1ed6","resolution":{"observed_at":"2026-08-04T14:50:30.959453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.18495","last_updated":"2024-12-09T20:21:56Z","snapshot_observed_at":"2026-08-06T04:32:59.039501Z","submitted_at":"2024-06-26T16:58:20Z","title":"WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.18495","snapshot_observed_at":"2026-08-04T14:50:30.962745Z","title":"Wildguard: Open one-stop moderation tools for safety risks, jailbreaks, and refusals of llms, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.962745Z"},"links":{"cited_paper":"/paper/2406.18495","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:e617fed4ecc56ba5769c8ba2706ec300015ec88d0e8085faeeada04b954846db","observation_id":"1e2d498e-0219-490a-815a-c3e32549f14a","resolution":{"observed_at":"2026-08-04T14:50:30.962745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04799","last_updated":"2024-06-07T06:28:05Z","snapshot_observed_at":"2026-08-06T08:33:44.603323Z","submitted_at":"2023-10-07T13:34:21Z","title":"Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04799","snapshot_observed_at":"2026-08-04T14:50:30.966421Z","title":"Chat vector: A simple approach to equip llms with instruction following and model alignment in new languages","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.966421Z"},"links":{"cited_paper":"/paper/2310.04799","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:a84155542faeb2b6e34d9a79a45f6e6b692661fcd203ec03d90084d521d34cc2","observation_id":"91f748cc-25cf-4579-8b24-217300e4883f","resolution":{"observed_at":"2026-08-04T14:50:30.966421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-04T14:50:30.969946Z","title":"Gpt-4o system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.969946Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:762af67ac4f4a14af70135335d5c513caa7e64d5f07ff131ec198a4036ddbb6e","observation_id":"c23e73fc-4789-457f-a297-f84903085429","resolution":{"observed_at":"2026-08-04T14:50:30.969946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.973764Z","title":"Wildguardmix-test-ko dataset","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.973764Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:2d8459b56c7a1e32d1ffd8d002877e451e59006a8a19183fd184c65f9a536e1c","observation_id":"916ddd2a-198d-4800-bcdd-26e01ddbc66f","resolution":{"observed_at":"2026-08-04T14:50:30.973764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.04089","last_updated":"2023-03-31T15:27:01Z","snapshot_observed_at":"2026-08-03T22:12:27.993418Z","submitted_at":"2022-12-08T05:50:53Z","title":"Editing Models with Task Arithmetic","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.04089","snapshot_observed_at":"2026-08-04T14:50:30.976797Z","title":"Editing models with task arithmetic","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.976797Z"},"links":{"cited_paper":"/paper/2212.04089","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:2d45ebf466546ee35c120f8e4667bbbd40d7eb7250905ccf119f8e30c024accd","observation_id":"88938e90-a2d8-40a1-9b1c-986a5efcb3b9","resolution":{"observed_at":"2026-08-04T14:50:30.976797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-04T14:50:30.980248Z","title":"Openai o1 system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.980248Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:976042f5cb2c1b06ecbc119e322e3d61259e01734e82be7e04d9c19901dbaf31","observation_id":"2c624e4e-7ccd-4518-9cb7-062546c6eb6a","resolution":{"observed_at":"2026-08-04T14:50:30.980248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-04T14:50:30.983316Z","title":"The llama 3 herd of models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.983316Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:e14a95ebd491249f4096d2e6c7b589f79965012902e8c128f4e16b5d17589392","observation_id":"f2527b49-f053-4a1d-8d09-695ce836588c","resolution":{"observed_at":"2026-08-04T14:50:30.983316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.986411Z","title":"Llama-guard-4-12b","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.986411Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:728188e990c7df2a0917cd432c219f9615cce6cfeebdf8434927a2ee5cee4d6d","observation_id":"e349ff9f-d93d-44fd-9fec-69a585b1f8c8","resolution":{"observed_at":"2026-08-04T14:50:30.986411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-09T20:34:52.923500Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-04T14:50:30.989044Z","title":"Decoupled weight decay regularization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.989044Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:8d1155003b22964c3159ff0f541b68ff42f68c684f5f712cd650ff22f5d9fb0b","observation_id":"03ff63b5-9738-4b12-8cac-0864b55f331c","resolution":{"observed_at":"2026-08-04T14:50:30.989044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.03274","last_updated":"2023-02-14T19:39:32Z","snapshot_observed_at":"2026-08-07T19:48:41.914424Z","submitted_at":"2022-08-05T16:47:23Z","title":"A Holistic Approach to Undesired Content Detection in the Real World","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.03274","snapshot_observed_at":"2026-08-04T14:50:30.992141Z","title":"A holistic approach to undesired content detection","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.992141Z"},"links":{"cited_paper":"/paper/2208.03274","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:ae0f042cf22a5e4cc12e9092e1530c84eb9cf9d1fab488660ac8459c925cd364","observation_id":"17a36167-b357-4480-bee9-490901646137","resolution":{"observed_at":"2026-08-04T14:50:30.992141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.07842","last_updated":"2023-02-15T18:25:52Z","snapshot_observed_at":"2026-07-30T02:11:00.198428Z","submitted_at":"2023-02-15T18:25:52Z","title":"Augmented Language Models: a Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.07842","snapshot_observed_at":"2026-08-04T14:50:30.995225Z","title":"Augmented language models: a survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.995225Z"},"links":{"cited_paper":"/paper/2302.07842","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:662dbb1bb1ac3806bff69c8dfa0cc7cd86954c419f9b91366e780a3e75adc2d5","observation_id":"fd5bd482-19a1-46e2-b9df-a3357130535f","resolution":{"observed_at":"2026-08-04T14:50:30.995225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:30.998272Z","title":"Content filtering overview","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:30.998272Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:aa53994aec821715aafc2d03f27c6621c46408675d0c07b2af8a206c56b6908d","observation_id":"2b872c27-537e-4e35-b3b1-2cc708ac2cb4","resolution":{"observed_at":"2026-08-04T14:50:30.998272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.001004Z","title":"kor\\_ethical\\_question\\_answer","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.001004Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:27eed38bc6b6a4eeaefe44b626fafc6eb1ab6299fbc3acb9dade0e66e6ec30eb","observation_id":"ce12c55c-b2b7-4a53-97e6-91db241ade07","resolution":{"observed_at":"2026-08-04T14:50:31.001004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07143","last_updated":"2024-08-09T22:37:25Z","snapshot_observed_at":"2026-08-02T14:27:24.212588Z","submitted_at":"2024-04-10T16:18:42Z","title":"Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07143","snapshot_observed_at":"2026-08-04T14:50:31.003990Z","title":"Leave no context behind: Efficient infinite context transformers with infini-attention","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.003990Z"},"links":{"cited_paper":"/paper/2404.07143","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:e69bae5f58a09cf87089175f7f53ecdb4ef0cdf0c2a1fb62b2ec706b575e9189","observation_id":"c81485f2-a133-48ee-8279-96f1666e2fa5","resolution":{"observed_at":"2026-08-04T14:50:31.003990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.007280Z","title":"llama3-instructrans-enko-8b, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.007280Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:d8bd5034f801ee5c79d1af90deaee2d7c3b92d4122114935413c20dc5d113c75","observation_id":"97d16b7c-2784-483a-b2eb-d2a051b75c15","resolution":{"observed_at":"2026-08-04T14:50:31.007280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.010321Z","title":"Llama-varco-8b-instruct","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.010321Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:c8a544d638a9620789b9a249bcdd92ca10f1755d318506d73e085a8da8a06e95","observation_id":"fbfbcb8e-7874-4416-9146-70f58471a126","resolution":{"observed_at":"2026-08-04T14:50:31.010321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.013221Z","title":"Configuration guide — nvidia nemo guardrails (streaming fields)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.013221Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:c7fac0008984d1f4417dc558914ea543177816639bedfaf083555a6a4cb313bc","observation_id":"3c9cd9e2-5866-449e-a854-6138b1889ca0","resolution":{"observed_at":"2026-08-04T14:50:31.013221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.016391Z","title":"Streaming — nvidia nemo guardrails (user guide)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.016391Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:1c7c4414ead132ed929811072dc3596c735abdf5ad97b5a9d2208a6e6aa758d7","observation_id":"fba5ee2e-acbd-4338-b829-7e6781dddf84","resolution":{"observed_at":"2026-08-04T14:50:31.016391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.019184Z","title":"Openai preparedness framework, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.019184Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:4ca256a115883b4a6a37a840877673b4b0cd2002aca6514853803a6bdad828de","observation_id":"ff4b1a7d-b82f-4295-8248-b66ee46ff0be","resolution":{"observed_at":"2026-08-04T14:50:31.019184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.023946Z","title":"Gpt-5 system card, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.023946Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:308b5b1b52e4dea1de0e3334c4b7a4600ff328b513dbb9e9e712530d50c01128","observation_id":"ff111a60-23fa-4639-ab3a-d93ae1ff5bb0","resolution":{"observed_at":"2026-08-04T14:50:31.023946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.027049Z","title":"Tool learning with large language models: A survey","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.027049Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:c192d2d4c2f605ce294115a09e5773fb7141b27c69cb8749d057d87f1b338a3c","observation_id":"4a31b7af-69a7-40cd-9fc8-a9021167f436","resolution":{"observed_at":"2026-08-04T14:50:31.027049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.01263","last_updated":"2024-04-01T11:50:35Z","snapshot_observed_at":"2026-08-03T00:58:55.865010Z","submitted_at":"2023-08-02T16:30:40Z","title":"XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.01263","snapshot_observed_at":"2026-08-04T14:50:31.029785Z","title":"Xstest: A test suite for identifying exaggerated safety behaviours in large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.029785Z"},"links":{"cited_paper":"/paper/2308.01263","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:39403b9be2d4f7c4b0eadf5647122ce9cc67c763023bd2b2dc9f5caa2f0201c4","observation_id":"19a211ca-e46e-46ae-8a45-214f2b85e9ef","resolution":{"observed_at":"2026-08-04T14:50:31.029785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.033984Z","title":"Llama-3.1-korean-8b-instruct","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.033984Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:3a87a080cb20e077948f3c9011b2435fbd20f00720134213cd3c236ef5af5d33","observation_id":"48d602e5-1e7c-4d89-934f-c0980d4c5d96","resolution":{"observed_at":"2026-08-04T14:50:31.033984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11679","last_updated":"2024-12-16T11:38:23Z","snapshot_observed_at":"2026-08-06T09:07:11.838772Z","submitted_at":"2024-12-16T11:38:23Z","title":"Bias Vector: Mitigating Biases in Language Models with Task Arithmetic Approach","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.11679","snapshot_observed_at":"2026-08-04T14:50:31.037378Z","title":"Bias vector: Mitigating biases in language models with task arithmetic approach","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.037378Z"},"links":{"cited_paper":"/paper/2412.11679","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:067232a6c0ded8985da962d235236c00e7ca9e97548f540aea4e90b3070173f1","observation_id":"4d38a7b1-9c3d-4e5f-ba61-6da7fa0c3a2e","resolution":{"observed_at":"2026-08-04T14:50:31.037378Z","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":"2026-08-04T14:50:31.040613Z","title":"Gemma 2: Improving open language models at a practical size","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.040613Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:672082ce88aef2f7835cc951e9882fec74626dd32c47b35eb42c9b955691d930","observation_id":"1b4dccd2-ccd5-4438-8872-cd4cfa094e0c","resolution":{"observed_at":"2026-08-04T14:50:31.040613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.043348Z","title":"Kanana safeguard, May 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.043348Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:49ea3b579a5de0ba6189b458ec0b64568d5461a39ae3e7e7c639516f99273323","observation_id":"b7acb2fe-8f06-4f35-b5ce-f23e83ccdb9f","resolution":{"observed_at":"2026-08-04T14:50:31.043348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.046176Z","title":"ko-gemma-2-9b-it, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.046176Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:d5c9e9464d9211e7ea611e4bf4304113b6f0b5022127b479d2da82dd9286a107","observation_id":"d542400a-edfb-4ed6-b2fb-2921678d778d","resolution":{"observed_at":"2026-08-04T14:50:31.046176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12241","last_updated":"2024-05-13T20:46:10Z","snapshot_observed_at":"2026-07-06T18:02:15.186390Z","submitted_at":"2024-04-18T15:01:00Z","title":"Introducing v0.5 of the AI Safety Benchmark from MLCommons","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12241","snapshot_observed_at":"2026-08-04T14:50:31.049227Z","title":"Introducing v0","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.049227Z"},"links":{"cited_paper":"/paper/2404.12241","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:c901a7c78937c4c6754113d7c0df00a596b33e09e8d39c932a93b3b452d2bd8c","observation_id":"0e07e347-5467-4664-a226-80b090c95822","resolution":{"observed_at":"2026-08-04T14:50:31.049227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.052233Z","title":"Llama3.1-8b-chinese-chat, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.052233Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:c4efbe23850ed9b127ad01c539b1209bdae55bff628107146da8946e1caf1905","observation_id":"f3cbfe49-9c0a-4811-900e-dbce42996647","resolution":{"observed_at":"2026-08-04T14:50:31.052233Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.04359","last_updated":"2021-12-08T16:09:48Z","snapshot_observed_at":"2026-08-09T15:17:43.394064Z","submitted_at":"2021-12-08T16:09:48Z","title":"Ethical and social risks of harm from Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.04359","snapshot_observed_at":"2026-08-04T14:50:31.055121Z","title":"Ethical and social risks of harm from language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.055121Z"},"links":{"cited_paper":"/paper/2112.04359","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:a177d5673b263f5d9300910f4d44afe91a70d4de5efa917141966e160be331f2","observation_id":"05eb3eba-4c23-4f6a-abb3-c494e220a785","resolution":{"observed_at":"2026-08-04T14:50:31.055121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17453","last_updated":"2024-04-07T00:56:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-29T17:59:56Z","title":"Efficient Streaming Language Models with Attention Sinks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17453","snapshot_observed_at":"2026-08-04T14:50:31.058629Z","title":"Efficient streaming language models with attention sinks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.058629Z"},"links":{"cited_paper":"/paper/2309.17453","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:d239bbeded185c4a0fa99d9d58cc20be131c2ecbed03e422be0a7ca9ab10572a","observation_id":"0a1cb17d-4c2d-4a95-ada5-d24f051f5925","resolution":{"observed_at":"2026-08-04T14:50:31.058629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.04745","last_updated":"2020-06-29T07:55:12Z","snapshot_observed_at":"2026-08-06T10:39:08.684653Z","submitted_at":"2020-02-12T00:33:03Z","title":"On Layer Normalization in the Transformer Architecture","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.04745","snapshot_observed_at":"2026-08-04T14:50:31.062172Z","title":"On layer normalization in the transformer architecture","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.062172Z"},"links":{"cited_paper":"/paper/2002.04745","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:44c03e1a8ad584545588d0dc8557e282f5b184e62f5ec1a16afbe9ca77f346a9","observation_id":"f511a1ad-1837-4de6-b872-298dbb6cd721","resolution":{"observed_at":"2026-08-04T14:50:31.062172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.01708","last_updated":"2023-10-27T01:09:31Z","snapshot_observed_at":"2026-07-06T15:37:16.278040Z","submitted_at":"2023-06-02T17:31:32Z","title":"TIES-Merging: Resolving Interference When Merging Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.01708","snapshot_observed_at":"2026-08-04T14:50:31.065384Z","title":"Ties-merging: Resolving interference when merging models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.065384Z"},"links":{"cited_paper":"/paper/2306.01708","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:d3491b086896ce0ce1057ed34da9f68c11d509844d64f63aaaa877e036273ea9","observation_id":"2a5b647f-e273-4dd5-89ab-d881efb971b5","resolution":{"observed_at":"2026-08-04T14:50:31.065384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21772","last_updated":"2024-08-04T22:13:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-31T17:48:14Z","title":"ShieldGemma: Generative AI Content Moderation Based on Gemma","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21772","snapshot_observed_at":"2026-08-04T14:50:31.068603Z","title":"Shieldgemma: Generative ai content moderation based on gemma","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.068603Z"},"links":{"cited_paper":"/paper/2407.21772","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:bdca60d996701a2ad71a1989c3097050875ae3112e6b2bf20a4fd7807470cadd","observation_id":"fdc5fc01-f68b-446a-9f36-d568292ec477","resolution":{"observed_at":"2026-08-04T14:50:31.068603Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17864","last_updated":"2024-06-25T18:13:05Z","snapshot_observed_at":"2026-07-06T18:37:00.469355Z","submitted_at":"2024-06-25T18:13:05Z","title":"AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17864","snapshot_observed_at":"2026-08-04T14:50:31.071555Z","title":"Ai risk categorization decoded (air 2024): From government regulations to corporate policies","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.071555Z"},"links":{"cited_paper":"/paper/2406.17864","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:5f6a8bec99eedc12b92df983d62633776a8589992b8bba8f4dd94a906d9c3a59","observation_id":"5cce258b-5973-497e-8972-8ee108a434c1","resolution":{"observed_at":"2026-08-04T14:50:31.071555Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18491","last_updated":"2025-04-13T06:16:49Z","snapshot_observed_at":"2026-08-04T13:17:25.983525Z","submitted_at":"2024-10-24T07:25:29Z","title":"ChineseSafe: A Chinese Benchmark for Evaluating Safety in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18491","snapshot_observed_at":"2026-08-04T14:50:31.075209Z","title":"Chinesesafe: A chinese benchmark for evaluating safety in large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.075209Z"},"links":{"cited_paper":"/paper/2410.18491","citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:41a9e484e8bdc0c813003b0e00dbf0fc7fe3a8e6d97d2090caf3b056f6314c8c","observation_id":"5f4c36af-b570-42a9-a0d2-a030a3c3b492","resolution":{"observed_at":"2026-08-04T14:50:31.075209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.078552Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.078552Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:a167309cbfaab645bb67c2525c3f0c40a79af9cea7f80f04ebf3eda8a24a4a9f","observation_id":"8add1a0b-badf-48bd-bd1b-0778cebb3f8a","resolution":{"observed_at":"2026-08-04T14:50:31.078552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.082139Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.082139Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:bad092e43571761a6f421ebfdb582a3e501726245b2c74e5450f299d79ce746a","observation_id":"baa0a3f5-5184-464c-9567-151cebcdb598","resolution":{"observed_at":"2026-08-04T14:50:31.082139Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.097455Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.097455Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:3b2b23d41f3dbba055e74ba5ecfe17eef65bad3f6279e80cd3b9edfea01fa816","observation_id":"b0dabfce-3c80-46a6-a892-84fd33815290","resolution":{"observed_at":"2026-08-04T14:50:31.097455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T14:50:31.100765Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-04T14:50:31.100765Z"},"links":{"citing_paper":"/paper/2509.23381"},"observation_digest":"sha256:72e5b52c9fb633f0241198c0c38306f0f9cb810cd1c5d7800239bbf1a7739910","observation_id":"87b5ae40-d8ca-40e8-b066-3bcb1df3d44c","resolution":{"observed_at":"2026-08-04T14:50:31.100765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.23381","last_updated":"2026-07-21T08:03:44Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T13:04:37.446062Z","submitted_at":"2025-09-27T16:03:44Z","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":47,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":47},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2509.23381."}