{"as_of":"2026-08-11T20:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ee67ab0d8f52b695ecc89893cd7cb12b2ae816d4b32cfeed9103d5cfd5adb261","coverage":[{"denominator":27,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:21:11.332334Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T16:10:09.106003Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T16:10:09.201963Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"cited_work":{"arxiv_id":"2501.03264","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.03264","snapshot_observed_at":"2026-08-05T16:10:09.201963Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","venue":"cs.LG","work_id":"a4437eb0-e27e-47f5-b8cd-0463f278c2de","year":2025},"citing_paper":{"arxiv_id":"2508.18903","last_updated":"2025-08-26T10:19:36Z","snapshot_observed_at":"2026-08-09T10:02:55.217768Z","submitted_at":"2025-08-26T10:19:36Z","title":"Distance-informed Neural Processes","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T16:10:09.106003Z"},"links":{"cited_paper":"/paper/2501.03264","citing_paper":"/paper/2508.18903"},"observation_digest":"sha256:a9aa3c0ee9a3a86fa7b7d45fe8e998dc9e47325fa8bda90c191c18e827142350","observation_id":"0021a57a-9aed-4be0-9904-2fa6b3b4dc72","resolution":{"observed_at":"2026-08-05T16:10:09.208359Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.03264/citation-record","integrity":"/paper/2501.03264/integrity","json":"/paper/2501.03264/citation-record.json","paper":"/paper/2501.03264"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:21:11.618732Z","title":null,"venue":null,"work_id":"cbe9c361-398c-40bf-a0be-188aac53effb","year":2015},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.283803Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:ffc58c1227975e43ca1d932fa560ff0eaab77d6cd6e658695aef7a7260525870","observation_id":"77bde9d6-18dd-4679-a729-87347c5ce11d","resolution":{"observed_at":"2026-08-10T22:21:11.621823Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.574278Z","title":"Let z ∈ Rd be the latent variable for a diagonal Gaussian conditional prior p(z|DC τ ; ϑ) = N (z; µϑ(DC τ ), Σϑ(DC τ ))","venue":null,"work_id":"48c82f83-9694-4dfb-8fd7-c1ec35debb06","year":2013},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.298901Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:5e7a45c9134ce8a03ea4bf8f7d619c49d1b1b50e56c5524c9897e5047e062546","observation_id":"31f0712b-5f25-481b-8f00-f3fc996ea378","resolution":{"observed_at":"2026-08-10T22:21:11.577912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.527885Z","title":null,"venue":null,"work_id":"641093b4-1dcc-4bfc-8a04-1b4e099d7fc4","year":2019},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.313571Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:1f3280a57e15583b9c8821ebf0e55e246dab0131095a1461ba34b823d2dceb0a","observation_id":"010a4b40-92ca-4a6c-9acb-885c86fa41cf","resolution":{"observed_at":"2026-08-10T22:21:11.531686Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-10T22:21:11.252956Z","title":"Auto-encoding variational bayes","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.252956Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:0c441a41fa21a1cf8e15ed5f8adf998335791e237e18fbbb117c46a692686323","observation_id":"61de20ad-e74d-497e-aa4c-1f8da5e22385","resolution":{"observed_at":"2026-08-10T22:21:11.252956Z","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":"2026-08-10T22:21:11.669200Z","title":null,"venue":null,"work_id":"dc746c45-687b-4cdd-8b85-bb6184932d7f","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.261049Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:c63960741d56e8af5bcd4c59b23839fff35b26667d8e78b3307eab708ad3bc47","observation_id":"87114b25-946b-4d86-8bec-4cb233ca8225","resolution":{"observed_at":"2026-08-10T22:21:11.672686Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.658115Z","title":"3 3.2 Evaluation Criteria & Asymptotic Performance","venue":null,"work_id":"b8f00616-9291-47ad-9210-d129e84f6b33","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.268935Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:ab0b94baf27dcc5792a7c7a7db108cc5b92539f8a2cd4b6daa2806eba509aa03","observation_id":"00cb6a24-27fe-4591-87f7-fb08c92d74ee","resolution":{"observed_at":"2026-08-10T22:21:11.661896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.638096Z","title":null,"venue":null,"work_id":"f914310b-1d3f-45fc-8002-70317b654a58","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.276410Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:227fadd507898b4a6caf4caa517af461fe75ca641e6339b02fa3a214b005ffaf","observation_id":"b99f0446-966e-4d28-8014-297a50695e76","resolution":{"observed_at":"2026-08-10T22:21:11.641101Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.628376Z","title":"Prior Distribution","venue":null,"work_id":"b87b5973-b7ac-4a01-ae81-4a5e88481b3c","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.280172Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:75de833dfefc1edac941a3c4eea6ecd5595e5af8cfa89ccbdcfb7a1062275a20","observation_id":"b7599d21-29da-43d9-9260-8284a66de0b9","resolution":{"observed_at":"2026-08-10T22:21:11.631439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.608478Z","title":null,"venue":null,"work_id":"bbe939d8-6ff4-46b0-8aa6-e023be4c4155","year":2018},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.287359Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:d8fb4da3cda3bf971ab2ef9b3eac7fdafd6c1a4058b5218d9da4ff03f4659dbc","observation_id":"8f625e7c-7d88-47dc-ba48-2a1d05f754f3","resolution":{"observed_at":"2026-08-10T22:21:11.612129Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.585431Z","title":"Here we denote the approximate inference gap byDAI KL and the posterior approximation gap by DPA KL in Table (5)","venue":null,"work_id":"6707fe8b-4dca-4283-8d07-b3fdf387072a","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.294895Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:26d80fb6e868d15d69f42c0504d546de4e2c191d4392b84c79efb90259fccb4c","observation_id":"7a454eda-752d-4376-ae9b-8d1f4f06752a","resolution":{"observed_at":"2026-08-10T22:21:11.589244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.562991Z","title":"To enable researchers to implement our developed method in studies, we leave the anonymous Github link here: https://anonymous.4open","venue":null,"work_id":"a11c15c5-3bd4-490d-807a-2a7264f49c74","year":2020},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.302683Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:609f38602b9c1f7e94145a5f080735ae5e40aa58fa7f56692322af905f2b61d1","observation_id":"e51d65d5-5d14-4f2a-aeaf-972740143f09","resolution":{"observed_at":"2026-08-10T22:21:11.566997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.539412Z","title":"G.2 N EURAL ARCHITECTURES & OPTIMIZATIONS & E VALUATION SET-UP Synthetic Regression","venue":null,"work_id":"d2308b6e-7f75-4979-8c05-035e7a823f25","year":2019},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.309991Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:40c37cb0577281123d02557151ee2a0bdb850150ee121ca3d21470f7b0fb47de","observation_id":"1ffc11da-f596-44dd-9410-6bbb596f0c80","resolution":{"observed_at":"2026-08-10T22:21:11.543425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.515932Z","title":null,"venue":null,"work_id":"61c29d04-e671-42fa-9047-11340cdc2b2d","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.317326Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:17e9644616a249dfa9f81a3d4bd6b604a34659dcc55fa9ce4d8e60688da1a417","observation_id":"590809bf-9571-4f93-9edd-e139456524a9","resolution":{"observed_at":"2026-08-10T22:21:11.519697Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.504467Z","title":"Our developed SI-NPs can be viewed as the conditional version of importance weighted autoen- coders, which explains the empirical observations in Fig","venue":null,"work_id":"17970499-1688-4896-a1f6-4c0327d0397b","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.320990Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:0cbb8b91164197b22cabbb8fab600505dbff18592541a9b516a81c3ae13b0897","observation_id":"3ac92f89-e496-445d-ba0c-cbc4085eab6d","resolution":{"observed_at":"2026-08-10T22:21:11.508475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.491374Z","title":"To enable fair comparison, we also augment other baselines with attention networks","venue":null,"work_id":"adf3190f-d020-4f4e-9268-45a1708d04a3","year":2019},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.324778Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:bcaccb69d429aeab9f31862323cc43b1e1172ae2a56e5cfbe58fa55862ad4842","observation_id":"9d1238d7-4d9e-4b3f-a7bc-08d650f815d5","resolution":{"observed_at":"2026-08-10T22:21:11.495803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.479918Z","title":"We notice that the SI-ANP significantly beats other models in FMNIST/SVHN/CIFAR10 and is comparable with the ML-ANP in MNIST","venue":null,"work_id":"19b027e1-9aaa-4a8a-bd3b-b9cc92994e84","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.328583Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:296f4010ec0606dfc57d26a8e37db20cc43ed300c3b90b1180cf03fdd3e56893","observation_id":"327160f7-325a-4b9f-9d62-e25a80e9cf70","resolution":{"observed_at":"2026-08-10T22:21:11.483918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.468817Z","title":"For each run, we randomly sample 1000 functions as tasks to evaluate","venue":null,"work_id":"3bb83e42-f9dc-4ae5-b5a4-344ebac20459","year":1935},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.332334Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:22b7d1965233391790e321a77e8b81337bece9c9568ae73b032ea458b4eed607","observation_id":"10fb7dbd-7451-4231-b8d5-0a11d280f34b","resolution":{"observed_at":"2026-08-10T22:21:11.472606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1406.2751","last_updated":"2015-04-16T17:22:58Z","snapshot_observed_at":"2026-07-06T03:46:02.568340Z","submitted_at":"2014-06-11T00:44:31Z","title":"Reweighted Wake-Sleep","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1406.2751","snapshot_observed_at":"2026-08-10T22:21:11.233595Z","title":"Reweighted wake-sleep","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2006,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.233595Z"},"links":{"cited_paper":"/paper/1406.2751","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:91226882d1bbc1335a8dfd59657265c03dca8b08ec0ec436dbde22194f40f174","observation_id":"0919fd3b-349e-426e-b7e6-c8e963853d15","resolution":{"observed_at":"2026-08-10T22:21:11.233595Z","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":"2026-08-10T22:21:11.551463Z","title":null,"venue":null,"work_id":"36b92d37-3f09-4eff-9424-c356dac17ab9","year":2012},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.306323Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:2311522b16e59c7af134ad9fcc2177f5c83c48c0f3709e14621a4f9267d79b37","observation_id":"0c3978e4-74bd-47e6-ad69-14efd7ba2d72","resolution":{"observed_at":"2026-08-10T22:21:11.555174Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.05850","last_updated":"2019-08-10T19:46:56Z","snapshot_observed_at":"2026-08-07T21:39:06.061314Z","submitted_at":"2019-06-13T17:49:54Z","title":"Reweighted Expectation Maximization","version":2},"cited_work":{"arxiv_id":"1906.05850","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.05850","snapshot_observed_at":"2026-08-10T22:21:11.448063Z","title":"Reweighted Expectation Maximization","venue":"stat.ML","work_id":"6e94d5b9-014d-4189-a51d-e6535b5c5f2d","year":2019},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.237835Z"},"links":{"cited_paper":"/paper/1906.05850","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:dd99d5bb559d415cd588a5b88ca947c13d2a8923f0c1d19c9fbf07141c5154e4","observation_id":"95530254-52bc-42cf-94c3-06a0bceef7de","resolution":{"observed_at":"2026-08-10T22:21:11.451440Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00734","last_updated":"2022-05-23T20:17:46Z","snapshot_observed_at":"2026-08-10T09:49:47.968247Z","submitted_at":"2021-01-04T01:29:09Z","title":"Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.00734","snapshot_observed_at":"2026-08-10T22:21:11.249383Z","title":"Factor analysis, probabilistic principal component analysis, variational inference, and variational autoencoder: Tutorial and survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.249383Z"},"links":{"cited_paper":"/paper/2101.00734","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:5421eb510f770ad9273383a9226d5b4db5dafd8ba365787c6b3a71335c67b44e","observation_id":"bf79d17a-e353-47a7-8aaf-8e32b22f7147","resolution":{"observed_at":"2026-08-10T22:21:11.249383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.03753","last_updated":"2020-10-08T04:10:05Z","snapshot_observed_at":"2026-08-10T19:12:52.170803Z","submitted_at":"2020-10-08T04:10:05Z","title":"Uncertainty in Neural Processes","version":1},"cited_work":{"arxiv_id":"2010.03753","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.03753","snapshot_observed_at":"2026-08-10T22:21:11.376975Z","title":"Uncertainty in Neural Processes","venue":"cs.LG","work_id":"bb3f5239-5d2c-42e3-89e5-b6691aa2dbef","year":2020},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.256898Z"},"links":{"cited_paper":"/paper/2010.03753","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:540a0707d69258f5c2a047f12996e3d5583fe00dd0e6b671228720c4f7c2e8e5","observation_id":"c2b68634-da62-4153-a9b2-4117cb51de46","resolution":{"observed_at":"2026-08-10T22:21:11.382356Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.596827Z","title":"In other words, the consistent regularizer in NPs is ill-posed for optimization","venue":null,"work_id":"bba467e6-2dca-462a-b7d6-8b590adfb655","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.291115Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:ff325da30ad961033dd9514fd6ce549c347267ed11b8267eb614c8dff72b5b6c","observation_id":"c24e3a49-7e14-42e2-ad08-1988ae658f57","resolution":{"observed_at":"2026-08-10T22:21:11.601190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T22:21:11.647405Z","title":"Since the meta learning exper- iment is computationally expensive and time-consuming in training processes, we do not examine combinations with other inductive biases in this paper","venue":null,"work_id":"65c90a97-5ce9-476d-80ae-8810e097c2c9","year":2023},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.272860Z"},"links":{"citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:0adba290b528d52cfa64bdd724cf60da0d73e74be7811be5dc9b9ad3c26caa3a","observation_id":"65d37e6a-243e-4479-ae62-368c7285b5b4","resolution":{"observed_at":"2026-08-10T22:21:11.650914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.11907","last_updated":"2019-06-12T11:38:15Z","snapshot_observed_at":"2026-07-06T07:42:13.977835Z","submitted_at":"2019-03-28T11:57:54Z","title":"Meta-Learning surrogate models for sequential decision making","version":2},"cited_work":{"arxiv_id":"1903.11907","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.11907","snapshot_observed_at":"2026-08-10T22:21:11.429727Z","title":"Meta-Learning surrogate models for sequential decision making","venue":"stat.ML","work_id":"6f666043-72bb-4740-8d08-85b2725fdb8d","year":2019},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.241624Z"},"links":{"cited_paper":"/paper/1903.11907","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:e5d361c135d7cd130481b454c826da390df4e1ae7b131b7ae28297cf44ead695","observation_id":"24600a56-2803-4ab5-8c39-6b67cf45bb68","resolution":{"observed_at":"2026-08-10T22:21:11.435014Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.01622","last_updated":"2018-07-04T14:49:46Z","snapshot_observed_at":"2026-08-07T09:28:44.794062Z","submitted_at":"2018-07-04T14:49:46Z","title":"Neural Processes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.01622","snapshot_observed_at":"2026-08-10T22:21:11.245306Z","title":"Conditional neural processes","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.245306Z"},"links":{"cited_paper":"/paper/1807.01622","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:844d62c3617bd9fedc4745823b2e849f48b5807f1aeb4e9e9af138ccf47d10bf","observation_id":"795110b5-b90c-42a0-92bd-19751bf0c9b7","resolution":{"observed_at":"2026-08-10T22:21:11.245306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-07-06T05:56:41.814255Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-10T22:21:11.264826Z","title":"Fashion-mnist: a novel image dataset for benchmark- ing machine learning algorithms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-10T22:21:11.264826Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/2501.03264"},"observation_digest":"sha256:240998a6626463ecc3da99255073dfb13f6724062a09fe043244d6e0c445f580","observation_id":"7924397e-18fe-4aec-8df7-13e4f305757b","resolution":{"observed_at":"2026-08-10T22:21:11.264826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.03264","last_updated":"2025-01-04T03:28:21Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T22:12:01.507782Z","submitted_at":"2025-01-04T03:28:21Z","title":"Bridge the Inference Gaps of Neural Processes via Expectation Maximization"},"reference_resolution":{"displayed":27,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":3,"verified_fuzzy":12},"total_outbound_references":27},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2501.03264."}