{"as_of":"2026-08-15T09:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:424578e621af6a72b105d131da1bfbda04e196547e33c4b46ad9714b90388eea","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:32:20.153108Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/2505.15252/citation-record","integrity":"/paper/2505.15252/integrity","json":"/paper/2505.15252/citation-record.json","paper":"/paper/2505.15252"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:28.748983Z","title":"R., Geist, M., and Bachem, O","venue":null,"work_id":"cb5046e2-d766-4de9-ac2f-d6618d08f0ae","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:13.554086Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:4bf45dce0a10b1fe97bb5736f29614fdec48ec86a28f5b8e52865cc25df11794","observation_id":"600a8bde-ad89-418c-a938-0c4de4cd0f75","resolution":{"observed_at":"2026-08-07T15:32:28.797779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:28.485730Z","title":"What is qwen llm","venue":null,"work_id":"77bece9c-d2f1-40d7-8d7b-6c78c675bc25","year":2025},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:13.663823Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:8d8ef9298f2d1e4bd5a9d4e98b7a1f7c64f15f90f7d01130e0cb73802e38c8d7","observation_id":"a4cb3292-9832-4405-b15e-f4f41d97cb4b","resolution":{"observed_at":"2026-08-07T15:32:28.629155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:28.330458Z","title":"Comparison of models: Quality, performance & price analysis","venue":null,"work_id":"f51cd876-5c4f-4872-a519-74213f6905c0","year":2025},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:13.789339Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:56a34eb536292396323a62d8837a8866053b517a7d0e2abbee72ff1a8403cf8b","observation_id":"3c10d16e-beb7-40db-8e2a-ba1dc2d05f06","resolution":{"observed_at":"2026-08-07T15:32:28.392416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:28.157333Z","title":"(leveled) fully homomorphic encryption without bootstrapping","venue":null,"work_id":"c00dc1a0-af29-47b6-a98e-182c06c1a6e4","year":2014},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:13.982112Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:3b9161ecc02af9a295963687d7d6080300e414db0c19d418fc678ed80c160629","observation_id":"ef2beccb-4744-446b-b5da-95dede977674","resolution":{"observed_at":"2026-08-07T15:32:28.233602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.984005Z","title":"D., Chen, D., and Dao, T","venue":null,"work_id":"f39b5107-936e-4b10-bdfd-7c6e03b757c4","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.148771Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:254e619e0e52fbadd64fae8867bff3f2a46f4bb692707eaad6a10347def24b84","observation_id":"e0495d4e-6648-4740-b63c-f94a14904c3e","resolution":{"observed_at":"2026-08-07T15:32:28.060555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.887798Z","title":"Ezpc: Programmable, efficient, and scalable secure two-party computation","venue":null,"work_id":"0725ef85-aa67-4bf4-b21a-6daf314494dc","year":2017},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.298536Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:3864afc1d7af2da804a8a4988a4151ae80d9faf8ec955d0e86764363d95e0f9d","observation_id":"3cdb21dc-d63a-4a96-9c0d-1c4dbb98a3f1","resolution":{"observed_at":"2026-08-07T15:32:27.933614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.00216","last_updated":"2022-06-02T01:06:12Z","snapshot_observed_at":"2026-08-13T15:32:41.261591Z","submitted_at":"2022-06-01T03:49:18Z","title":"THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.00216","snapshot_observed_at":"2026-08-07T15:32:14.400102Z","title":"The-x: Privacy-preserving transformer inference with homomorphic encryption","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.400102Z"},"links":{"cited_paper":"/paper/2206.00216","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:39e3217d01ec794f329259965bb90186883aeb36b043db9aef146dbdfa189f51","observation_id":"469c814c-aebb-4860-b4d0-c70034bcb198","resolution":{"observed_at":"2026-08-07T15:32:14.400102Z","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":"2026-08-07T15:32:27.814922Z","title":"and Gao, Q","venue":null,"work_id":"19b30709-daf5-44da-8772-31253fce5283","year":2022},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.487461Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:b7af98690ea01eb434a483895de39601eefa8ab05d22deb7045c9fe45dac51fd","observation_id":"b1aad603-a0ea-495a-bfc8-f83227d5d99e","resolution":{"observed_at":"2026-08-07T15:32:27.844156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:14.644570Z","title":"E., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.644570Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:7182dafc15ed3c5bd6b313f9efecc263f743b5484e1c5afa45c9b7bd0bac1049","observation_id":"3010204b-834f-4e90-830b-492283af3278","resolution":{"observed_at":"2026-08-07T15:32:14.644570Z","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":"2026-08-07T15:32:14.729334Z","title":"W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.729334Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:70f1906ad4bddcf98b995bd4b6231968a64b2789901b7c0be10802c979e8f67b","observation_id":"756fca72-e133-4299-ae8a-ff30d980f126","resolution":{"observed_at":"2026-08-07T15:32:14.729334Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T15:32:14.822821Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.822821Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:0263a6610bb4157b98cbb5256f4d84ad76ebdd797a72663c5c273cb4480f026d","observation_id":"adef9e4d-a23f-4d18-8cf5-5014a02edc95","resolution":{"observed_at":"2026-08-07T15:32:14.822821Z","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":"2026-08-07T15:32:14.939168Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:14.939168Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:e7935c75e183ae82715f1802a4d749b006dfa059c336eae23e9ad8398825796c","observation_id":"7e333e8b-8004-468a-b74d-a90aad8bf5c1","resolution":{"observed_at":"2026-08-07T15:32:14.939168Z","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":"2026-08-07T15:32:15.063805Z","title":"Puma: Secure inference of llama-7b in five minutes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.063805Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:af6028e4637401f853d63b102470c48a3c92ab349c5fe1de58a0dab262242684","observation_id":"33cd7897-c608-4325-88f4-dc0abb98402c","resolution":{"observed_at":"2026-08-07T15:32:15.063805Z","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":"2026-08-07T15:32:27.660935Z","title":"Learning transformer programs","venue":null,"work_id":"eb4d8504-2b0b-4587-8c2a-8f4838758ed5","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.160771Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:e484f642add708d1014acc54c61b64c587e70b6773de08c622dd356182932bbf","observation_id":"265c7447-c2a9-4c76-9362-1d03231bc46f","resolution":{"observed_at":"2026-08-07T15:32:27.713709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.508787Z","title":"finance-alpaca (revision 51d16b6), 2024","venue":null,"work_id":"231e29de-720b-4804-8c94-4ab7c07d93d4","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.265622Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:ac586145e4be1abece828541cdbef435fa7b6ea70a92375d5bedff7663459abf","observation_id":"07d4fc02-6568-4e66-8379-fc9502d40a01","resolution":{"observed_at":"2026-08-07T15:32:27.572067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.339273Z","title":"Fully homomorphic encryption using ideal lattices","venue":null,"work_id":"1b4378b8-aa13-4aea-b77c-39644a9d36f9","year":2009},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.371810Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:828657c1bd02c0a72b92ebe0cafc157c5682edd9eca7b7821f333c2723f6e344","observation_id":"7f56e231-2fcc-4f8d-a9c1-72c2387e9403","resolution":{"observed_at":"2026-08-07T15:32:27.399635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.189963Z","title":"Introducing palm 2","venue":null,"work_id":"d4d65973-9163-4594-9f1b-f32b7ef8288b","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.425241Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:630b857a70051e8fece21cdf6b26045c06abdd1c9376bc7bc49e62818e68143c","observation_id":"fa740b53-78d5-4b22-b83c-56d2017a731d","resolution":{"observed_at":"2026-08-07T15:32:27.249352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:27.066472Z","title":"Github copilot, 2025","venue":null,"work_id":"d6b7aef6-cc84-4da3-b6f8-60a155e5851f","year":2025},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.517484Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:57432077f899337a520c6980f668879aef6e8e6b62562a5bc80209f4f307a63a","observation_id":"285e3af6-aa92-4af1-b32f-aa14820b2ae1","resolution":{"observed_at":"2026-08-07T15:32:27.115764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:26.917932Z","title":"Sigma: secure gpt inference with function secret sharing","venue":null,"work_id":"e485d925-b812-406f-ab00-4d41162596ea","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.639220Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:4867aaaa9c29e8cca01a92d8e1aeba0c99de186be52dac8457633355cba84120","observation_id":"906955c2-7197-4821-a05e-8f75b856db7f","resolution":{"observed_at":"2026-08-07T15:32:26.986978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:26.760177Z","title":"Iron: Private inference on transformers","venue":null,"work_id":"f5308533-efa6-46fc-b33e-68180df1f277","year":2022},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.717753Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:5989fa3b2af0ba59eb78cd2e8fc7470412cf548bd3c0fb5de42a9cb209bf7df1","observation_id":"06a705a7-c14c-4d45-aa93-544b519be80b","resolution":{"observed_at":"2026-08-07T15:32:26.827758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:26.617813Z","title":"Rhombus: Fast homomorphic matrix-vector multiplication for secure two-party inference","venue":null,"work_id":"29bc1b8d-fc47-40c7-ab1d-fa481ce03c04","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.796903Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:9734897e1593eff886626de91db17081ad3cfd70987c52bc3f7c9b4a25824d91","observation_id":"f731d97e-1238-48b9-bffd-bfb07b840c6a","resolution":{"observed_at":"2026-08-07T15:32:26.678817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:26.479864Z","title":"Ciphergpt: Secure two-party gpt inference","venue":null,"work_id":"6e84222f-0ad0-4bd4-a0ef-8999fa41104f","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.867196Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:65312eb974d9809f4a84a2190ac480b99bf46ceaf62ba784a7239ebd2a7f212c","observation_id":"9cadbab9-47f6-4977-98a1-cd4aa7b7f9a9","resolution":{"observed_at":"2026-08-07T15:32:26.541110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.09436","last_updated":"2020-06-08T09:09:28Z","snapshot_observed_at":"2026-08-06T10:54:14.530969Z","submitted_at":"2019-09-20T11:52:45Z","title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.09436","snapshot_observed_at":"2026-08-07T15:32:15.949174Z","title":"Codesearchnet challenge: Evaluating the state of semantic code search","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:15.949174Z"},"links":{"cited_paper":"/paper/1909.09436","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:b5e1f7b9bcbd5d7b69adb80718ea4fc20a7a17492bae8fee9ebdec86b51645e7","observation_id":"c11fe372-5d09-4561-ab36-f82ac7164a1f","resolution":{"observed_at":"2026-08-07T15:32:15.949174Z","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":"2026-08-07T15:32:26.278469Z","title":"Extending oblivious transfers efficiently","venue":null,"work_id":"70cdaa8c-09f0-493c-85d1-c3f2dd4740e1","year":2003},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.072311Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:122e8afc1debc9df1e5e2e70f3ed63187e2203eda4fbf011f91b7b19bcfecdfd","observation_id":"c3c425a9-d919-4926-9475-562c4f999271","resolution":{"observed_at":"2026-08-07T15:32:26.388735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:26.089423Z","title":"\\ GAZELLE \\ : A low latency framework for secure neural network inference","venue":null,"work_id":"fbbcbe46-56e0-4bf3-815c-d96002a3d1c3","year":2018},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.191260Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:a5dc99911862b08ae5ea2b081d192dfc97cd1bd74a648d195e5ffc6817b5f823","observation_id":"2102655f-6a70-4bd6-8b56-4b01319d5be1","resolution":{"observed_at":"2026-08-07T15:32:26.166595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:16.278823Z","title":"Dense passage retrieval for open-domain question answering","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.278823Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:8ff7af3ba71b94ad72f04e798566cc7e79c738b1c8a2c38cbf1e54cd118f2cc3","observation_id":"1f01ca15-8553-47ee-96ce-a8b59c307c33","resolution":{"observed_at":"2026-08-07T15:32:16.278823Z","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":"2026-08-07T15:32:25.879167Z","title":null,"venue":null,"work_id":"2994da38-b921-42eb-a410-5a4a24ed45a1","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.397004Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:81b5387b94c85e49313e5ce37969d69c1487576d00e504bbc4eedc8bee1a396d","observation_id":"97272f47-c9de-4847-9b99-36917a4e0600","resolution":{"observed_at":"2026-08-07T15:32:25.951975Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:25.704864Z","title":"and Kumaresan, R","venue":null,"work_id":"33f28a56-cc0e-4b40-94e3-fbce81220afb","year":2013},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.494588Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:cfa61276692f42b6f1a840f374e9e89af4ce160c0f010abe1323b0492e479246","observation_id":"b4249a31-088a-49f4-bb25-74876cb11fdc","resolution":{"observed_at":"2026-08-07T15:32:25.765576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13795","last_updated":"2023-02-20T15:43:22Z","snapshot_observed_at":"2026-08-13T12:40:49.900534Z","submitted_at":"2023-02-20T15:43:22Z","title":"ChatGPT: A Meta-Analysis after 2.5 Months","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13795","snapshot_observed_at":"2026-08-07T15:32:16.612491Z","title":"Chatgpt: A meta-analysis after 2.5 months","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.612491Z"},"links":{"cited_paper":"/paper/2302.13795","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:4c67e49c24b89d91e5e654903d3e00afa83eae972f0fcbac1d079cfcf9707169","observation_id":"2d585509-2bda-4164-b406-cc5e4c7d1cd0","resolution":{"observed_at":"2026-08-07T15:32:16.612491Z","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":"2026-08-07T15:32:16.730707Z","title":"Fast inference from transformers via speculative decoding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.730707Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:f6ce086f1772172b80d58cf2c4fd928dc7fc76d27da1ecf7cd51e83d86004e5c","observation_id":"f38d7e25-208e-4596-adcd-6b5e38a68c07","resolution":{"observed_at":"2026-08-07T15:32:16.730707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01452","last_updated":"2023-03-16T06:51:31Z","snapshot_observed_at":"2026-08-14T00:22:06.250115Z","submitted_at":"2022-11-02T19:43:22Z","title":"MPCFormer: fast, performant and private Transformer inference with MPC","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.01452","snapshot_observed_at":"2026-08-07T15:32:16.795973Z","title":"P., and Zhang, H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.795973Z"},"links":{"cited_paper":"/paper/2211.01452","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:c0cb8bfa79c917d1d2fa05920fc5dc158a4141ab64e18823dde3053279129f7e","observation_id":"38baee99-de64-49c4-8300-5ea8c4c2a68e","resolution":{"observed_at":"2026-08-07T15:32:16.795973Z","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":"2026-08-07T15:32:25.434988Z","title":"Seesaw: Compensating for nonlinear reduction with linear computations for private inference","venue":null,"work_id":"3d296d62-0acd-4e34-bc14-a050856e682c","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.882366Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:cb13ed3e2a384edf91a5ed23eb7c5288d41e864679ebac5053a57802d59a03d0","observation_id":"013e7d99-6869-47a2-b66b-6145e8b3f7db","resolution":{"observed_at":"2026-08-07T15:32:25.547644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15707","last_updated":"2024-11-24T04:24:31Z","snapshot_observed_at":"2026-08-15T06:26:47.367285Z","submitted_at":"2024-11-24T04:24:31Z","title":"Nimbus: Secure and Efficient Two-Party Inference for Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15707","snapshot_observed_at":"2026-08-07T15:32:16.991061Z","title":"Nimbus: Secure and efficient two-party inference for transformers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:16.991061Z"},"links":{"cited_paper":"/paper/2411.15707","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:7ecadd842e29782c79d7d311a0bf892022a83d3587c505f7ff85da9da237a0f9","observation_id":"5c7df084-7362-4596-abb7-4583d980545b","resolution":{"observed_at":"2026-08-07T15:32:16.991061Z","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":"2026-08-07T15:32:25.237800Z","title":"Merge: Fast private text generation","venue":null,"work_id":"fc155bbf-eb91-4d32-b191-608e57f1356c","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.110890Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:0f16b8d5db0d171e9de1d868d60b4fc8d790c2fcf7b3910d1957ea46c9382ec6","observation_id":"55ebc46c-cce8-4e01-86de-f17ef65ef759","resolution":{"observed_at":"2026-08-07T15:32:25.331728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:25.033231Z","title":"Online speculative decoding","venue":null,"work_id":"2d7a7f4f-3f15-4ea8-9f7d-1dde20aae51b","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.211128Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:2de882f888324ff7f239e702d5cacc777d8c3f54782f88980dba4fd31f8541cd","observation_id":"3232671e-baf6-4bb8-95b8-e8278bf107ca","resolution":{"observed_at":"2026-08-07T15:32:25.132385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:24.829390Z","title":"BumbleBee: Secure Two-party Inference Framework for Large Transformers","venue":null,"work_id":"c2274497-c701-4216-8929-ce412e4a4c51","year":2025},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.357344Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:5c78863b57c1c280df6a9d31fcea5a3010c7e65a79eb38ee6332a0317ed0cef6","observation_id":"33ac2324-d8bc-4d99-864c-0cd33580ea03","resolution":{"observed_at":"2026-08-07T15:32:24.941674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:24.632350Z","title":"On ideal lattices and learning with errors over rings","venue":null,"work_id":"8a141db4-b51b-4729-b0f4-0d46904b8645","year":2010},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.463858Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:f91de3cb458e0aca7a3eeb3882cf1016174fb25936f2047104da1ac7a84beae6","observation_id":"36c68217-7c6a-4a34-ac6f-6de2f344c1ab","resolution":{"observed_at":"2026-08-07T15:32:24.717428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:24.414187Z","title":"\\ SecretFlow-SPU \\ : A performant and \\ User-Friendly \\ framework for \\ Privacy-Preserving \\ machine learning","venue":null,"work_id":"99f5f6f6-befa-487e-a038-2843bd3e1b81","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.569661Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:2b55892726076a73737843ef358d9712832822f8fe41216d065da4ee54098cb1","observation_id":"48430fe9-ffc5-4196-8eea-0811e305f143","resolution":{"observed_at":"2026-08-07T15:32:24.516940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:24.110006Z","title":null,"venue":null,"work_id":"2548a03f-8c0e-46dc-ac41-485263d0ef77","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.726784Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:5c591dd5bb1865e22c3454ce50f4a7f62149ca5d3aab1a0148305e10b33d728a","observation_id":"c8960fa6-6ef4-490b-9131-a8352006021f","resolution":{"observed_at":"2026-08-07T15:32:24.256218Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:23.805949Z","title":null,"venue":null,"work_id":"4054f078-0635-4834-973b-73ab58219e05","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.840403Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:314b8c8f5c957a906387bf6f46f51aaa930298103332ffc5fa78b89a0a743cb8","observation_id":"bd612572-290b-4203-9428-40a72a1bbba6","resolution":{"observed_at":"2026-08-07T15:32:23.927840Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:23.479315Z","title":"Api pricing, 2025","venue":null,"work_id":"8deaed32-190b-471a-b91f-4d3cbb77bca0","year":2025},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:17.924318Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:588556319d36b3f00fc7d3f6fddaa97c7c4d13cee207990845947de068678c97","observation_id":"69267277-cd63-4c46-9fee-c8dc82267453","resolution":{"observed_at":"2026-08-07T15:32:23.640472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:23.217792Z","title":"Bolt: Privacy-preserving, accurate and efficient inference for transformers","venue":null,"work_id":"6d354e5c-c360-4f60-b470-c38ca63dadd8","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.060976Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:aa4398703cc1b3ef98d00a6b7dad5a7439fba6a1355593d9b363b77d80635d48","observation_id":"37b30ce6-8582-4fb0-8f38-abcd21592b83","resolution":{"observed_at":"2026-08-07T15:32:23.361291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:18.171536Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.171536Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:d13ba9408166203e979438f737d129901b357d05a807ed204b3d73f755285335","observation_id":"5d201a5d-dd74-4212-a041-daac23eaaea0","resolution":{"observed_at":"2026-08-07T15:32:18.171536Z","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":"2026-08-07T15:32:23.052075Z","title":"Spencnn: orchestrating encoding and sparsity for fast homomorphically encrypted neural network inference","venue":null,"work_id":"f6948bde-48c0-411c-b717-3a5a403068cf","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.257625Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:5d702799145b428c17eacc7882546307a64aa75ef6e0cd7baf19bf6b130c49bd","observation_id":"a95398c6-a160-4bd7-8919-f26eb0dce9fb","resolution":{"observed_at":"2026-08-07T15:32:23.097016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:22.712406Z","title":null,"venue":null,"work_id":"4da628df-64cf-4354-ba89-f6b9109d1dbc","year":2019},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.354424Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:1e017cc5ce942d16fbe113af7375e6eb0ad3e828dbae5a7f236b9aec77ef70de","observation_id":"6d858c2e-691a-4419-87d3-77d208ddbbf2","resolution":{"observed_at":"2026-08-07T15:32:22.920808Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:22.301451Z","title":"Cryptflow2: Practical 2-party secure inference","venue":null,"work_id":"5de91af3-e81b-47f2-b19b-cbb07bb44615","year":2020},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.454408Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:8d0e6606f1e1de8b19895624aa7cbf8bb22e9cb5d9fb213a50fbf1af52dd6be2","observation_id":"4ca1a078-90bb-4058-9f72-8e4cf0468294","resolution":{"observed_at":"2026-08-07T15:32:22.515787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:21.949255Z","title":null,"venue":null,"work_id":"a502451e-ebf1-4f21-9455-8d4cf44fb494","year":2021},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.573316Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:c5a38cd70716ea488bc3a314872fbfb8177ea0debfa40c97a6bbfc2c43093959","observation_id":"3d58d1f7-8870-44ca-8f0e-9ef3fc27accb","resolution":{"observed_at":"2026-08-07T15:32:22.125359Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:21.682336Z","title":"A., Manoel, A., Mireshghallah, F., Lin, Z., Gopi, S., Kulkarni, J., and Sim, R","venue":null,"work_id":"ac6a5bea-0a6e-42ba-8a00-0de94b9d6f83","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.683870Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:accfd9f3b197c030a47b8d3cbdf5b74065793f8f5671cbdfaa609fd479d4df2f","observation_id":"0055e514-44a6-4b5b-8010-9cb281a75df2","resolution":{"observed_at":"2026-08-07T15:32:21.807987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.10686","last_updated":"2022-01-30T16:42:46Z","snapshot_observed_at":"2026-08-14T18:21:00.075690Z","submitted_at":"2021-09-22T12:29:15Z","title":"Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.10686","snapshot_observed_at":"2026-08-07T15:32:18.828359Z","title":"W., Narang, S., Yogatama, D., Vaswani, A., and Metzler, D","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.828359Z"},"links":{"cited_paper":"/paper/2109.10686","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:79da2b7d829bcfed82b2a2392a69bbee2958a144447d5fd858ed69dcb12a5550","observation_id":"4b3b7d66-e4a5-42fb-8d59-7cbebfbb1b7c","resolution":{"observed_at":"2026-08-07T15:32:18.828359Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-07T15:32:18.905924Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:18.905924Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:1bb9ee4d67945bc10f8f765d01c42a13f8206e01d3c1320c7c295f6656829b3d","observation_id":"455034cd-a71d-44f8-9eb9-5d7f2f22e75c","resolution":{"observed_at":"2026-08-07T15:32:18.905924Z","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":"2026-08-07T15:32:19.030549Z","title":"N., Kaiser, ., and Polosukhin, I","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.030549Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:fa38cda94f92a8cc6d560a507361ac396b902bd3c6d12b156d8c90b22458a911","observation_id":"f42f346c-1c7b-481d-957d-5758482702df","resolution":{"observed_at":"2026-08-07T15:32:19.030549Z","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":"2026-08-07T15:32:21.429761Z","title":"Transformers are uninterpretable with myopic methods: a case study with bounded dyck grammars","venue":null,"work_id":"a0eb9245-4df1-4807-b7e9-fe8b416f5e26","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.163195Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:85daec0f9b385e0ab9e24fafa859ed1e3b69a1f1097b59962d586420d1c80e83","observation_id":"520e54bf-e3fa-456d-8f3a-f74f688f1d3d","resolution":{"observed_at":"2026-08-07T15:32:21.524782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T15:32:21.270135Z","title":"CCN et: Extracting high quality monolingual datasets from web crawl data","venue":null,"work_id":"f876f381-da50-4a16-9602-079742691c9e","year":2020},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.243807Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:e569b2e26d5fffeb3ebdc9f15633ccaa62f51bbf41d16d053426b65eb4e19935","observation_id":"ee64ae86-d0f4-40bf-a77a-3451d23aa089","resolution":{"observed_at":"2026-08-07T15:32:21.347652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03771","last_updated":"2020-07-14T03:42:34Z","snapshot_observed_at":"2026-07-06T08:27:58.343233Z","submitted_at":"2019-10-09T03:23:22Z","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03771","snapshot_observed_at":"2026-08-07T15:32:19.329333Z","title":"Huggingface's transformers: State-of-the-art natural language processing","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.329333Z"},"links":{"cited_paper":"/paper/1910.03771","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:488ad5ac81bab293a41b7b417569d7411c28b57c08d952b0cc6a8f88d9a79e06","observation_id":"3f5c9f1e-670e-467f-964a-4fc702633feb","resolution":{"observed_at":"2026-08-07T15:32:19.329333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14569","last_updated":"2024-10-29T02:20:24Z","snapshot_observed_at":"2026-08-12T23:59:51.199798Z","submitted_at":"2024-05-23T13:44:48Z","title":"PrivCirNet: Efficient Private Inference via Block Circulant Transformation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14569","snapshot_observed_at":"2026-08-07T15:32:19.466145Z","title":"Privcirnet: Efficient private inference via block circulant transformation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.466145Z"},"links":{"cited_paper":"/paper/2405.14569","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:f888e6963c5ae80ce3e5ec176a84394cb27d3a7c11aa384efcfd92a773bb551a","observation_id":"10994473-3e09-478a-aa80-c3a9100fb463","resolution":{"observed_at":"2026-08-07T15:32:19.466145Z","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":"2026-08-07T15:32:21.028558Z","title":"Ferret: Fast extension for correlated ot with small communication","venue":null,"work_id":"262ba8db-7a59-4830-a754-ab75b0735f25","year":2020},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.608113Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:a93e9d86c01964b9ffd545aa4e215e95cfbed7e4208f69ca2834a7368e47b3c2","observation_id":"6a3f947a-1584-4be4-b7e0-a74c7b744961","resolution":{"observed_at":"2026-08-07T15:32:21.157190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:19.743257Z","title":null,"venue":null,"work_id":null,"year":1986},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.743257Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:ee8a85531d3cdecd9bd3c7a3bdf1a8b7099f29734f3cadb698e1d9c176c7e39c","observation_id":"432bff1d-967c-470d-a2f6-af0a5a5d86ec","resolution":{"observed_at":"2026-08-07T15:32:19.743257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.08887","last_updated":"2019-02-02T23:53:18Z","snapshot_observed_at":"2026-08-14T18:24:27.863819Z","submitted_at":"2018-09-24T13:03:13Z","title":"Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.08887","snapshot_observed_at":"2026-08-07T15:32:19.836448Z","title":"Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.836448Z"},"links":{"cited_paper":"/paper/1809.08887","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:bb42c73b8cade11985315c7dc4628d5d5a232a28a83ac6bff25f88f8a5440332","observation_id":"ae82251c-df5f-4584-8f21-3c008ab643cc","resolution":{"observed_at":"2026-08-07T15:32:19.836448Z","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":"2026-08-07T15:32:20.831391Z","title":"Mpcvit: Searching for accurate and efficient mpc-friendly vision transformer with heterogeneous attention","venue":null,"work_id":"c1cbc986-7590-4f44-9fa1-fa71de7aa89d","year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.914363Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:a2adc4e241591aa31a74c7f74cfc5e18495fd8d82fd9bea07b791d65402c93c3","observation_id":"cbf1c940-1e6b-4c3b-8a45-f2c55b33aeea","resolution":{"observed_at":"2026-08-07T15:32:20.936617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-14T10:40:26.323157Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-07T15:32:19.992494Z","title":"X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:19.992494Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:c1afa0fc57194d4a9d7aa485ce867e4dd205c5a8149cb2cf79c8e4c30ea733ae","observation_id":"ee84852d-1479-4d71-aaa2-cb9a49f2bfa0","resolution":{"observed_at":"2026-08-07T15:32:19.992494Z","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":"2026-08-07T15:32:20.568485Z","title":"Converting transformers to polynomial form for secure inference over homomorphic encryption","venue":null,"work_id":"b1f08249-9add-4743-8806-179830473d79","year":2024},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:20.083826Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:a8f317077dd89aac54e070b6a885f043744070ca7411056420ce76f9a22c7b5e","observation_id":"f6deca3b-496c-42d5-8888-e6ec253b2531","resolution":{"observed_at":"2026-08-07T15:32:20.683860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:32:20.153108Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-07T15:32:20.153108Z"},"links":{"citing_paper":"/paper/2505.15252"},"observation_digest":"sha256:fed0779fcd1e2de5c7252f3dc507482549e053086189e6579d3bb5f196706740","observation_id":"e5a5f14b-f681-4d7c-881d-d5fa6cbeb97b","resolution":{"observed_at":"2026-08-07T15:32:20.153108Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.15252","last_updated":"2025-05-21T08:28:56Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-13T16:39:04.833781Z","submitted_at":"2025-05-21T08:28:56Z","title":"An Efficient Private GPT Never Autoregressively Decodes"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":0,"verified_fuzzy":35},"total_outbound_references":62},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2505.15252."}