{"as_of":"2026-08-13T14:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d5ac6d28f99bf921d027171a64118d9751db79abf0dbfe408b7fb8baf133e8e9","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:33:40.797312Z","state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T19:32:34.395038Z","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":"2026-05-17T22:22:08.967264Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11424","snapshot_observed_at":"2026-08-09T19:32:34.395038Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00306","last_updated":"2025-06-30T16:37:59Z","snapshot_observed_at":"2026-08-12T04:02:30.056679Z","submitted_at":"2025-02-01T04:01:18Z","title":"Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T19:32:34.395038Z"},"links":{"cited_paper":"/paper/2411.11424","citing_paper":"/paper/2502.00306"},"observation_digest":"sha256:f91b8c02458134f77ec369a9d2dd7c525a0a2172abcdb1d6eccf06d474050301","observation_id":"1d2e4c6b-c279-4e5d-8eef-13d67a5f192a","resolution":{"observed_at":"2026-08-09T19:32:34.395038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"cited_work":{"arxiv_id":"2411.11424","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.11424","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Membership inference attack against long-context large language models","venue":null,"work_id":"946376ab-9bb6-4d3a-9c31-f7e893c1f5f5","year":2024},"citing_paper":{"arxiv_id":"2511.13502","last_updated":"2026-05-07T21:01:36Z","snapshot_observed_at":"2026-08-11T15:53:54.234598Z","submitted_at":"2025-11-17T15:39:54Z","title":"SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-17T22:20:53.561649Z"},"links":{"cited_paper":"/paper/2411.11424","citing_paper":"/paper/2511.13502"},"observation_digest":"sha256:d33f98ccfbf1471365724d816e3750a4a28c04a83fa8a03bb92250e37f74f1ea","observation_id":"c8da911c-564c-4981-9df4-0b195e896928","resolution":{"observed_at":"2026-05-17T22:22:08.970714Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.11424/citation-record","integrity":"/paper/2411.11424/integrity","json":"/paper/2411.11424/citation-record.json","paper":"/paper/2411.11424"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-10T14:07:02.234322Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-12T18:33:40.685635Z","title":"Phi-3 technical report: A highly capable language model locally on your phone,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.685635Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:6f9c7b5cf13899610e35941a34907faab9520be7051708403b752bb5cba961f7","observation_id":"2583a5e7-6577-449a-b806-e527d7d5621a","resolution":{"observed_at":"2026-08-12T18:33:40.685635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04652","last_updated":"2025-01-21T10:12:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-03-07T16:52:49Z","title":"Yi: Open Foundation Models by 01.AI","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04652","snapshot_observed_at":"2026-08-12T18:33:40.690331Z","title":"Yi: Open foundation models by 01. ai,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.690331Z"},"links":{"cited_paper":"/paper/2403.04652","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:8ceaccc40f79a89a57efc5fc1a2ab6a3ecc91e2a59e663b8ef6148aaff0688da","observation_id":"17c644b9-54e5-4fe2-9c6a-db9a573818f6","resolution":{"observed_at":"2026-08-12T18:33:40.690331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08268","last_updated":"2025-02-03T21:47:31Z","snapshot_observed_at":"2026-08-11T03:45:32.889856Z","submitted_at":"2024-02-13T07:47:36Z","title":"World Model on Million-Length Video And Language With Blockwise RingAttention","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.08268","snapshot_observed_at":"2026-08-12T18:33:40.694057Z","title":"World model on million-length video and language with ringattention,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.694057Z"},"links":{"cited_paper":"/paper/2402.08268","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:680d4cc4e64c3dc31721186308195088aaa3f3d3262b939833c11d548125d61f","observation_id":"49c5b4c6-3567-42c7-bcaa-7cae94bfc474","resolution":{"observed_at":"2026-08-12T18:33:40.694057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-07-06T17:41:42.995949Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-12T18:33:40.697905Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.697905Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:4f798b13bc1cdba316097132c5505d2aba268f47837b1f113d1f8e38308978d0","observation_id":"c2d67ecb-7c00-45d5-b32c-281ca3710235","resolution":{"observed_at":"2026-08-12T18:33:40.697905Z","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":"2026-08-12T18:33:40.702118Z","title":"Large language models can be easily distracted by irrelevant context,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.702118Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:6a41369485a4d354264b985e70679ca6379f9951654966e5648f447179726848","observation_id":"cc81eafd-9156-4a26-b218-1317f81b03ba","resolution":{"observed_at":"2026-08-12T18:33:40.702118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02060","last_updated":"2024-06-12T02:46:16Z","snapshot_observed_at":"2026-08-13T00:39:10.515138Z","submitted_at":"2024-04-02T15:59:11Z","title":"Long-context LLMs Struggle with Long In-context Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02060","snapshot_observed_at":"2026-08-12T18:33:40.705220Z","title":"Long-context llms struggle with long in-context learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.705220Z"},"links":{"cited_paper":"/paper/2404.02060","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:24c682b3e0df8bb4206194587076c6a6ea44543ba7219a1bcfc2232754136a4d","observation_id":"bfc6ae88-c1d9-45d7-b507-f46d6a88d728","resolution":{"observed_at":"2026-08-12T18:33:40.705220Z","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":"2026-08-12T18:33:41.103013Z","title":"Lost in the middle: How language models use long contexts,","venue":null,"work_id":"8dd856c7-30a1-4e38-a3df-d1310621808c","year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.708851Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:e13347adbd8395d2fc756d91cf3f35bc50ecde80de8ea224da03b50cfadaa966","observation_id":"e16837e8-0b91-4054-9a3e-972b7f5ae9e4","resolution":{"observed_at":"2026-08-12T18:33:41.106057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:41.092675Z","title":"H2o: Heavy-hitter oracle for efficient generative inference of large language models,","venue":null,"work_id":"a31740db-78c3-4b13-8968-dc938837258a","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.711742Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:9bb432c26233772085e57e770f77971f85847d708a0e42b9b9b45d9a7c157765","observation_id":"3d0a9065-b01f-4270-a891-9ad321b3064a","resolution":{"observed_at":"2026-08-12T18:33:41.095977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14469","last_updated":"2024-06-17T03:01:58Z","snapshot_observed_at":"2026-08-07T22:57:56.263839Z","submitted_at":"2024-04-22T17:42:58Z","title":"SnapKV: LLM Knows What You are Looking for Before Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14469","snapshot_observed_at":"2026-08-12T18:33:40.714373Z","title":"Snapkv: Llm knows what you are looking for before generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.714373Z"},"links":{"cited_paper":"/paper/2404.14469","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:ab107e2b587a5567ae0a877a12ea758cc5aadf70c586630ddda80e4d29205a28","observation_id":"e8529df5-f120-4a02-9dc7-2ef17bf98582","resolution":{"observed_at":"2026-08-12T18:33:40.714373Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.17422","last_updated":"2024-09-25T23:14:47Z","snapshot_observed_at":"2026-08-12T22:37:21.042988Z","submitted_at":"2024-09-25T23:14:47Z","title":"Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.17422","snapshot_observed_at":"2026-08-12T18:33:40.717224Z","title":"Discovering the gems in early layers: Accelerating long-context llms with 1000x input token reduction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.717224Z"},"links":{"cited_paper":"/paper/2409.17422","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:de06ea8fc91a1b1516e2006b75452d47b8d40f204f7062c5f61f7a3092f5823f","observation_id":"f511c18c-6fd5-4b4f-8d43-f095d7c6dd26","resolution":{"observed_at":"2026-08-12T18:33:40.717224Z","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":"2026-08-12T18:33:41.082928Z","title":"Membership inference attacks against language models via neighbourhood comparison,","venue":null,"work_id":"902a7022-50d9-44a8-8ddd-539e4ad8d370","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.720214Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:53440d820fc82b4200f8571cf1fc5af1f7d192fd33f30a66a8cc773a47645f6d","observation_id":"96169d1a-c28c-4868-a25c-809d78227d44","resolution":{"observed_at":"2026-08-12T18:33:41.086633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:41.071264Z","title":"Detecting pretraining data from large language models,","venue":null,"work_id":"7e05c0cf-9662-4c7f-8c0c-f1ba62481e77","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.722741Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:90b168e00628e4aaee4ba9e892307bda1f9b814fc3bdb7250b3a3fae05308280","observation_id":"d425e6eb-dfb6-43b7-bcfe-cad800dfa4e3","resolution":{"observed_at":"2026-08-12T18:33:41.075440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:41.061777Z","title":"Practical membership inference attacks against large-scale multi-modal models: A pilot study,","venue":null,"work_id":"a96561c6-0146-48bb-9d1d-0c15fd6440ac","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.725948Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:9c6188dc1642c2cf4aa73d34ff294375145d905a65b786bc495af3d0977b8207","observation_id":"f37fe73e-4d3c-462f-89b2-87b31bf5e5df","resolution":{"observed_at":"2026-08-12T18:33:41.065629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-12T18:33:40.728761Z","title":"Llama: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.728761Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:36742cecfe98e955b5650f9c0b44ed3c3b803b28580a159f578c6b43f7845eeb","observation_id":"09086194-8d08-4f5e-b537-598850ec583a","resolution":{"observed_at":"2026-08-12T18:33:40.728761Z","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":"2026-08-12T18:33:40.732008Z","title":"Llama 2: Open foundation and fine-tuned chat models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.732008Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:08db680ba3741b6a41ef29a7af2680786cbdbd68eff1445b22d4dae7067fdbb1","observation_id":"54b6a18f-525e-4d19-b425-2a4bb838df20","resolution":{"observed_at":"2026-08-12T18:33:40.732008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.04906","last_updated":"2020-09-30T21:27:13Z","snapshot_observed_at":"2026-07-06T09:11:26.109763Z","submitted_at":"2020-04-10T04:53:17Z","title":"Dense Passage Retrieval for Open-Domain Question Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.04906","snapshot_observed_at":"2026-08-12T18:33:40.735343Z","title":"Dense passage retrieval for open-domain question answering,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.735343Z"},"links":{"cited_paper":"/paper/2004.04906","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:b077974fd5a5fa2bf99899b85fa7f15fbda4cd36e1746972036b3103aa45c3c2","observation_id":"c0ab9f54-4aad-4943-adab-2f2cc6bba87a","resolution":{"observed_at":"2026-08-12T18:33:40.735343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.01087","last_updated":"2021-06-08T12:39:49Z","snapshot_observed_at":"2026-08-03T19:06:45.958735Z","submitted_at":"2021-06-02T11:42:56Z","title":"Is Sparse Attention more Interpretable?","version":2},"cited_work":{"arxiv_id":"2106.01087","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.01087","snapshot_observed_at":"2026-08-12T18:33:40.900061Z","title":"Is Sparse Attention more Interpretable?","venue":"cs.CL","work_id":"ba5306f9-8831-4619-a2d2-3eb7d01e7f94","year":2021},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.738982Z"},"links":{"cited_paper":"/paper/2106.01087","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:48479e288b461c7d62fb40ac93e7b82ede29b8aee1d35c583da13c9673032a4f","observation_id":"c33f825d-5911-4f8d-beaf-60cd49368a8b","resolution":{"observed_at":"2026-08-12T18:33:40.905237Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02486","last_updated":"2023-07-19T12:25:35Z","snapshot_observed_at":"2026-08-13T11:02:07.325742Z","submitted_at":"2023-07-05T17:59:38Z","title":"LongNet: Scaling Transformers to 1,000,000,000 Tokens","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02486","snapshot_observed_at":"2026-08-12T18:33:40.742656Z","title":"Longnet: Scaling transformers to 1,000,000,000 tokens,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.742656Z"},"links":{"cited_paper":"/paper/2307.02486","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:7e4903b4de52228ec9b2d9b3a90c717f120ec85576892b4a984ac3271400cd87","observation_id":"28e4a46f-9e69-40a5-a043-8a1f2f89a575","resolution":{"observed_at":"2026-08-12T18:33:40.742656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.12409","last_updated":"2022-04-22T18:20:48Z","snapshot_observed_at":"2026-08-07T11:26:24.970964Z","submitted_at":"2021-08-27T17:35:06Z","title":"Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.12409","snapshot_observed_at":"2026-08-12T18:33:40.745593Z","title":"Train short, test long: Attention with linear biases enables input length extrapolation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.745593Z"},"links":{"cited_paper":"/paper/2108.12409","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:01c16451307cebf0b547f3a0dce1fc45f7dc9bc678b2a64772c094838a0b98cb","observation_id":"bb27b572-052b-4fa8-8491-5c9824c8c20e","resolution":{"observed_at":"2026-08-12T18:33:40.745593Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13753","last_updated":"2024-02-21T12:30:33Z","snapshot_observed_at":"2026-08-02T12:47:57.325302Z","submitted_at":"2024-02-21T12:30:33Z","title":"LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13753","snapshot_observed_at":"2026-08-12T18:33:40.749018Z","title":"Longrope: Extending llm context window beyond 2 million tokens,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.749018Z"},"links":{"cited_paper":"/paper/2402.13753","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:fbbbd06eaaec91d13a971dc4e2f1c25ee0e7f89e5264e610ac76253d7be22564","observation_id":"4427b648-554d-49ae-9648-5cff9eab4d78","resolution":{"observed_at":"2026-08-12T18:33:40.749018Z","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":"2026-08-12T18:33:40.752547Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.752547Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:42ec8e3f6873e9e67fe1d06b19dd9ca8bf3cf2587fc4025dd4b06fe3311fa115","observation_id":"e11bfb06-eeba-4fa3-b353-4dcce7f0a563","resolution":{"observed_at":"2026-08-12T18:33:40.752547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.03929","last_updated":"2022-11-04T02:47:37Z","snapshot_observed_at":"2026-08-10T22:04:02.030232Z","submitted_at":"2022-03-08T08:50:34Z","title":"Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.03929","snapshot_observed_at":"2026-08-12T18:33:40.755299Z","title":"Quantifying privacy risks of masked language models using membership inference attacks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.755299Z"},"links":{"cited_paper":"/paper/2203.03929","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:23eff0eef948246097ab48670e88b205b6c430699406059b4676154761937915","observation_id":"5cfe3787-ac17-43d1-9f68-3c153b81a3ef","resolution":{"observed_at":"2026-08-12T18:33:40.755299Z","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":"2026-08-12T18:33:41.046018Z","title":"Seeing is believing: Black-box membership inference attacks against retrieval augmented generation,","venue":null,"work_id":"3b1662d0-3a67-4bdd-8dbd-b252d421f56f","year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.758075Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:8ff165ed7856ef52fa94f50e31959a475f934308a2cc6a18eb0a2d1a50d44329","observation_id":"399279e2-bd02-483c-93b7-3f0dc37f5e5f","resolution":{"observed_at":"2026-08-12T18:33:41.049823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.20446","last_updated":"2025-02-04T14:35:38Z","snapshot_observed_at":"2026-08-12T23:53:46.298124Z","submitted_at":"2024-05-30T19:46:36Z","title":"Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.20446","snapshot_observed_at":"2026-08-12T18:33:40.761169Z","title":"Is my data in your retrieval database? membership inference attacks against retrieval augmented generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.761169Z"},"links":{"cited_paper":"/paper/2405.20446","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:f445dd6204abb0e0748635d76ba4b8461f3930eaf4881cd08b1dac2384afb90d","observation_id":"2b9c3a57-6ca6-4fb3-920d-40b04ebdd0f3","resolution":{"observed_at":"2026-08-12T18:33:40.761169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.01380","last_updated":"2024-09-02T17:23:23Z","snapshot_observed_at":"2026-08-12T22:52:54.058844Z","submitted_at":"2024-09-02T17:23:23Z","title":"Membership Inference Attacks Against In-Context Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.01380","snapshot_observed_at":"2026-08-12T18:33:40.764821Z","title":"Membership inference attacks against in-context learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.764821Z"},"links":{"cited_paper":"/paper/2409.01380","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:0c4acb4e945e6ade1162cd5f4bb749398fce13e6e206902a20af922d3c54575a","observation_id":"081ba1d7-3d6c-4185-b72d-baefb34e873a","resolution":{"observed_at":"2026-08-12T18:33:40.764821Z","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":"2026-08-12T18:33:41.035784Z","title":"Insights into llm long-context failures: When transformers know but don’t tell,","venue":null,"work_id":"ba12a854-612c-4bd5-a989-d89819bffdbc","year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.768275Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:d56a3a9570df066cf66bb9df1a20a7bf5c5d9c21111d3a76fe7c9c8873a2e808","observation_id":"3fef563b-6f86-42b9-b6ff-53ab227e40cf","resolution":{"observed_at":"2026-08-12T18:33:41.039284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:41.025515Z","title":"Bertscore: Evaluating text generation with bert,","venue":null,"work_id":"ff6c8809-7ce6-45b0-956c-bff858d93fcf","year":2020},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.771437Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:a720260570554157596336f4e6c89fbf6fd96a94a0342825f9d8386057e58c8f","observation_id":"b6a92b6a-c593-4cd2-b74d-ee7d765a9caa","resolution":{"observed_at":"2026-08-12T18:33:41.028943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:41.013912Z","title":"A call for clarity in reporting bleu scores,","venue":null,"work_id":"17099a76-c68b-41ed-a2de-5406832d4d42","year":2018},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.774365Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:e9efda80a3912030ccc00d0bc9bc34716b28a338855653390f242b79b4208788","observation_id":"80b3b936-b57d-4bef-8bbc-0e4a7897faf9","resolution":{"observed_at":"2026-08-12T18:33:41.018213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.14508","last_updated":"2024-06-19T04:00:32Z","snapshot_observed_at":"2026-08-08T03:49:18.086396Z","submitted_at":"2023-08-28T11:53:40Z","title":"LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.14508","snapshot_observed_at":"2026-08-12T18:33:40.777759Z","title":"Longbench: A bilingual, multitask benchmark for long context understanding,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.777759Z"},"links":{"cited_paper":"/paper/2308.14508","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:27f27f3d283a088031f9cc6ef91648b167553107e46b8bf1ff3730807d14329a","observation_id":"f448e06f-e38c-44f6-91c5-183127b73b77","resolution":{"observed_at":"2026-08-12T18:33:40.777759Z","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":"2026-08-12T18:33:41.002862Z","title":"How long can context length of open-source llms truly promise?","venue":null,"work_id":"de7edc21-552c-49f2-9ae3-1ff6c3dec330","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.781198Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:c82a75b863282fca32b6dcbe9fccca1fd0fef0f250145660247330c7efcb31cf","observation_id":"1ecd9407-c427-490f-9502-51ee07c16c48","resolution":{"observed_at":"2026-08-12T18:33:41.006529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T18:33:40.992318Z","title":"Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,","venue":null,"work_id":"860cd46a-effd-4242-a9ec-babef671b684","year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.784211Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:042c1358cd4ebf0ec82facc576a93ac485846892cfbb0ab603501d4f85f3edad","observation_id":"ffbcda91-bd7e-41e5-8cec-a41871857364","resolution":{"observed_at":"2026-08-12T18:33:40.996244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-12T18:33:40.786758Z","title":"Mistral 7b,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.786758Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:372e20dc601702a102501e963784035a057878f66cef60773455700751f4428e","observation_id":"4272ca92-e56b-46c3-a897-63911bdfce28","resolution":{"observed_at":"2026-08-12T18:33:40.786758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.08295","last_updated":"2024-04-16T12:52:47Z","snapshot_observed_at":"2026-08-03T03:29:01.959523Z","submitted_at":"2024-03-13T06:59:16Z","title":"Gemma: Open Models Based on Gemini Research and Technology","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.08295","snapshot_observed_at":"2026-08-12T18:33:40.789481Z","title":"Gemma: Open models based on gemini research and technology,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.789481Z"},"links":{"cited_paper":"/paper/2403.08295","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:1be1efdcf332c32cc950c044c04f8b9e428f2955565870bf5907f0df96313cd5","observation_id":"2b84b5cf-c15c-4d8c-9340-0ccf3004f163","resolution":{"observed_at":"2026-08-12T18:33:40.789481Z","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":"2026-08-12T18:33:40.792768Z","title":"Membership inference attacks against machine learning models,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.792768Z"},"links":{"citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:9adcfea8bef3e4ef53dd4a998c88fa978668d80127f305a59c9e5f1a7d23b554","observation_id":"a7b5402a-a543-4283-9fe7-5ecbc9f794d2","resolution":{"observed_at":"2026-08-12T18:33:40.792768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01100","last_updated":"2025-03-31T20:37:34Z","snapshot_observed_at":"2026-08-12T23:31:28.428984Z","submitted_at":"2024-07-01T09:06:57Z","title":"Eliminating Position Bias of Language Models: A Mechanistic Approach","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01100","snapshot_observed_at":"2026-08-12T18:33:40.797312Z","title":"Eliminating position bias of language models: A mechanistic approach,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T18:33:40.797312Z"},"links":{"cited_paper":"/paper/2407.01100","citing_paper":"/paper/2411.11424"},"observation_digest":"sha256:759e98e4900a6c4cdcbb9b67fb9e0326c0f4c65894b52ea17bcb8f0d94389fbe","observation_id":"980236e0-e84b-4e5a-a463-756518c25e67","resolution":{"observed_at":"2026-08-12T18:33:40.797312Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.11424","last_updated":"2024-11-18T09:50:54Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T18:29:30.513660Z","submitted_at":"2024-11-18T09:50:54Z","title":"Membership Inference Attack against Long-Context Large Language Models"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":1,"verified_fuzzy":11},"total_outbound_references":35},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 inbound Pith citation observations for arXiv:2411.11424."}