{"as_of":"2026-08-12T06:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ef3de6e06d984ab09fd4e494725396a67b749648be53fd59b2b781236ba417c","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T00:16:23.971894Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2412.19578/citation-record","integrity":"/paper/2412.19578/integrity","json":"/paper/2412.19578/citation-record.json","paper":"/paper/2412.19578"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:16:24.720283Z","title":"’virus and epidemic’: Causal knowledge activates prediction error circuitry,","venue":null,"work_id":"b5cf2a84-af3e-45ec-ab4a-9589be0eea81","year":2010},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.752601Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:072408645014f85d281d70d1f2d8a49f8c40c578bbbf08cdb3016ce3cbc6b995","observation_id":"3a3a2549-fe46-41d2-a711-f113477c7620","resolution":{"observed_at":"2026-08-11T00:16:24.725511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.10500","last_updated":"2019-12-23T16:20:53Z","snapshot_observed_at":"2026-08-11T15:41:29.745802Z","submitted_at":"2019-11-24T11:04:56Z","title":"Causality for Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.10500","snapshot_observed_at":"2026-08-11T00:16:23.758183Z","title":"Causality for machine learning,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.758183Z"},"links":{"cited_paper":"/paper/1911.10500","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:87de2697b318d55a99f56ac9658f8cb2e4f194c894d341bda1a4db797c8dbdb1","observation_id":"ff955741-3309-44b1-b9e1-f731c2592a0e","resolution":{"observed_at":"2026-08-11T00:16:23.758183Z","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":"2026-08-11T00:16:24.704413Z","title":"From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data,","venue":null,"work_id":"6e18cf6d-0e46-469b-aca1-c40eee75e5ef","year":2007},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.763602Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:5f20d052b0ebdacf9d0656982febf444ff136997969791ffabe04d3fe78eaf1c","observation_id":"c8541e12-0dbc-4d63-866b-0ed72ad9b053","resolution":{"observed_at":"2026-08-11T00:16:24.709101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.675716Z","title":"Learning bayesian networks is np-complete,","venue":null,"work_id":"cfc6294d-3fda-4b05-8da8-25ebb688dbb7","year":1995},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.773730Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:8880d473c64e05c3d8b17ed97db32887a1558401174bef19403b3a5dd3782932","observation_id":"8c4a33a6-91c8-48a5-9e08-398dda95d2bc","resolution":{"observed_at":"2026-08-11T00:16:24.680419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.659768Z","title":"Causal discovery with reinforcement learning,","venue":null,"work_id":"254919b8-b2eb-4b3c-8ddf-1f34e5ce4a07","year":2020},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.778167Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:934150a5a1aaf18291561885e34c8ac9edeca62da98dd510ef43c2e69b630cf0","observation_id":"1b896bf6-d886-47a0-bcdb-b22fd0ac4db3","resolution":{"observed_at":"2026-08-11T00:16:24.665410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.644271Z","title":"Estimating the Dimension of a Model,","venue":null,"work_id":"a4ce3e60-8c78-410c-ae2e-a9a47303a903","year":1978},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.783225Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:3f252c85d6ba29c72c413e6d424b170f27ecb9e98cac4f8179851e516e23b149","observation_id":"9371cffc-bcf2-452d-91f5-64dcaf609c99","resolution":{"observed_at":"2026-08-11T00:16:24.649157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:23.787518Z","title":"Simple statistical gradient-following algorithms for connectionist reinforcement learning,","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.787518Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:4c23819f62c61de3f0606cc7fe7e35c2d9d7d3a192d935259e5a5af309ea1f24","observation_id":"febd5bc0-497b-4bfc-9543-2341586f2a86","resolution":{"observed_at":"2026-08-11T00:16:23.787518Z","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":"2026-08-11T00:16:24.618185Z","title":"Policy gradient methods for reinforcement learning with function approxima- tion,","venue":null,"work_id":"51fddd43-2ff1-42d0-a337-2fa1e253e8cc","year":1999},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.791547Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:0288dad15bbcd199f2b4aae39f0fda68b0736ea7750f3d8addd38534fb12c557","observation_id":"52fcbfc4-dfbe-4116-be2f-c41d1f31ad12","resolution":{"observed_at":"2026-08-11T00:16:24.623325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.603096Z","title":"Trust region policy optimization,","venue":null,"work_id":"894d6d37-fccd-4246-ab61-2004904c4a0f","year":2015},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.795650Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:96ea36e675b2d1e3e05ddad8c46e3a9dd813e15dcfc9d122ffac348e5311c533","observation_id":"45ad2c72-b893-4585-8bdc-0b7879068ebd","resolution":{"observed_at":"2026-08-11T00:16:24.607836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-11T00:16:23.799849Z","title":"Proximal policy optimization algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.799849Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:a95ac8f6587b934e5493054fc5a933836b6fe67820557dc53fc806e54e123e80","observation_id":"8c17b5e1-f94a-4102-b573-00f3be016a21","resolution":{"observed_at":"2026-08-11T00:16:23.799849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10903","last_updated":"2018-02-04T19:13:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-10-30T12:41:12Z","title":"Graph Attention Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10903","snapshot_observed_at":"2026-08-11T00:16:23.804436Z","title":"Graph attention networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.804436Z"},"links":{"cited_paper":"/paper/1710.10903","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:1604cb13e2bb661fc96d1cdb7b0c6edf1218a7adc02a128922f35312c4420186","observation_id":"184215e8-a1fe-4b89-bc9b-cde8757cdc05","resolution":{"observed_at":"2026-08-11T00:16:23.804436Z","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":"2026-08-11T00:16:24.587554Z","title":"Approximating discrete probability distri- butions with dependence trees,","venue":null,"work_id":"965af0b8-a543-4bbb-a262-13ee9f182d2d","year":1968},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.809326Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:deaf61618852e51128c4ee79746025b186dc6260e9ce33876092aea4ac85ed52","observation_id":"e6086f89-8ebf-4d1b-b1a5-6b4ff46dc59f","resolution":{"observed_at":"2026-08-11T00:16:24.592433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.571950Z","title":"The max-min hill- climbing bayesian network structure learning algorithm,","venue":null,"work_id":"f8c57ec0-0a57-4e99-9397-624723697217","year":2006},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.813672Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:df8ab2f2e70c11d8c40489ab78bc74d1d5e2b1c96db44b86a9e9a68cba7c48ee","observation_id":"fb9157af-2389-48e6-9988-c8615c6d072e","resolution":{"observed_at":"2026-08-11T00:16:24.577328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.556243Z","title":"Dags with NO TEARS: continuous optimization for structure learning,","venue":null,"work_id":"f09fc0aa-24b2-43de-9075-949ff344b259","year":2018},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.817889Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:f8a9c8547cf29d5112b8d66ada46999d3f791744f48b6d4c9f20260794cda36f","observation_id":"56705c56-326f-447a-9fce-736049671ca8","resolution":{"observed_at":"2026-08-11T00:16:24.561268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.541518Z","title":"Generalized score functions for causal discovery,","venue":null,"work_id":"7045137e-ff93-483b-bf90-d52fba18e18c","year":2018},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.821978Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:6108a9900e28cc86e478682cfb270564810c1ff65133c89a9cc7fa18177d4998","observation_id":"2edb3afa-cd42-42fb-ab5d-63000d4ea8ae","resolution":{"observed_at":"2026-08-11T00:16:24.546004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.526425Z","title":"Causal discovery with continuous additive noise models,","venue":null,"work_id":"4cee812a-c921-43a6-a7d3-d3b6755937d9","year":2009},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.826339Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:acebe5215845e92e693ee3cc38791479dbb165afc37ad9e4e3810c0532deb404","observation_id":"0eb3bfb3-03a4-4702-91bd-6a9c8432d952","resolution":{"observed_at":"2026-08-11T00:16:24.531048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.509842Z","title":"A machine learning approach to classify pedestrians’ event based on imu and gps,","venue":null,"work_id":"4a4d5657-9604-4f13-b46d-e23475284b13","year":2019},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.830523Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:99b5dd22648d89726173d7343da682b4388f77cba258edfc869dafcc9b8853b4","observation_id":"6722d0b7-3f4a-4547-9fca-4b095dc4e057","resolution":{"observed_at":"2026-08-11T00:16:24.515118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.495083Z","title":"Deep learning versus traditional solutions for group trajectory outliers,","venue":null,"work_id":"2954af47-aa69-4575-849d-d0e50256218b","year":2020},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.834431Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:409992a6c1521c3cba34061a69e253194925e1d0ea899e49fa1acb6c59387f79","observation_id":"59d5b341-eccd-428b-b1a4-bedb5059e479","resolution":{"observed_at":"2026-08-11T00:16:24.499683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.480944Z","title":"Iterative feedback and learning control. servo systems applications,","venue":null,"work_id":"1b726c71-5213-462b-a058-89215927d3a5","year":2007},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.838574Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:f954fb3ba5a7a31283c5932a3914e24bf3fb7061cd9cd88a0558861d13af8565","observation_id":"3cb29365-e3df-43ec-84c6-f0e78576ddb2","resolution":{"observed_at":"2026-08-11T00:16:24.485467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.465247Z","title":"Adaptive ekf-based vehicle state estimation with online assessment of local observability,","venue":null,"work_id":"88c6c0f5-ac67-4c8d-ba18-1d34332827c7","year":2016},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.843198Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:00d9f1eb5fe6bf2b1b2d79cc9336fed529d2094cf2979a99ffaa1ed5d9673e88","observation_id":"e9db1719-3ca3-495b-a130-1d0e5326fa47","resolution":{"observed_at":"2026-08-11T00:16:24.470724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.449073Z","title":"Learning functional causal models with generative neural networks,","venue":null,"work_id":"cfeb3cb3-16ad-48f7-bb1b-9558a2ae6b4c","year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.847636Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:6b6412c841269c2b5eb3348cf503c85ee20bb9cf257a6e7247a0f4617f6a3c42","observation_id":"e89725c7-e918-4c75-a222-980e875ec994","resolution":{"observed_at":"2026-08-11T00:16:24.454424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.433054Z","title":"Structural Agnostic Modeling: Adversarial Learning of Causal Graphs,","venue":null,"work_id":"b0c442e6-f082-4300-8d1d-aacf7a67fae5","year":2018},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.851940Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:ccea756c504270599768696e7e6803438538458f95a238e953fbc9d17430bbbf","observation_id":"1c418afc-5b1b-461c-9e96-ac40a2a536df","resolution":{"observed_at":"2026-08-11T00:16:24.438071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.417354Z","title":"DAG-GNN: DAG structure learning with graph neural networks,","venue":null,"work_id":"daebd252-9dcf-4ea8-bbd5-c3586bf50c1d","year":2019},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.856592Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:53cc7617900707477fbb335503d79cc677c41ba5b1d6f1179df8432133a0b182","observation_id":"e9b72fbe-e06e-449c-8128-b9d876458032","resolution":{"observed_at":"2026-08-11T00:16:24.422505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.401534Z","title":"A new model for learning in graph domains,","venue":null,"work_id":"61832fa1-c4f2-4145-bdba-c7f8aff25b4a","year":2005},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.860901Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:7411c367091c1fc38c07596e25c95e702d74b0b18bbf9a55cb421de1f5aabcff","observation_id":"0f473df5-fa80-4f7f-b040-65900fe8814a","resolution":{"observed_at":"2026-08-11T00:16:24.406715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.385405Z","title":"The graph neural network model,","venue":null,"work_id":"515838a3-2a1b-4135-8e2a-6d1115f6d216","year":2009},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.865491Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:1bf78a450fc3caebc1920f9baf2ae3668dcf287d9269d688546b1e425d018d82","observation_id":"609e598e-6526-44aa-aff5-e6f6b2b2edb2","resolution":{"observed_at":"2026-08-11T00:16:24.391107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05467","last_updated":"2023-12-01T08:37:27Z","snapshot_observed_at":"2026-08-02T21:31:41.024748Z","submitted_at":"2019-11-07T06:30:47Z","title":"ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05467","snapshot_observed_at":"2026-08-11T00:16:23.869935Z","title":"Chebnet: Efficient and stable constructions of deep neural networks with rectified power units using chebyshev approximations,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.869935Z"},"links":{"cited_paper":"/paper/1911.05467","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:0554c838cacd357463c422ae7e2115502f8aa731149e5a4733bec7eb6a526908","observation_id":"cdb8993d-0427-4a39-9310-7688354fd097","resolution":{"observed_at":"2026-08-11T00:16:23.869935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.02216","last_updated":"2018-09-10T14:26:58Z","snapshot_observed_at":"2026-08-10T12:30:48.918405Z","submitted_at":"2017-06-07T14:51:05Z","title":"Inductive Representation Learning on Large Graphs","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.02216","snapshot_observed_at":"2026-08-11T00:16:23.874792Z","title":"Inductive representation learning on large graphs,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.874792Z"},"links":{"cited_paper":"/paper/1706.02216","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:2d9a1567f87b3553a785d62e5c0d70f4ec7200f16dee748c1c188dbee24bfffc","observation_id":"ea85c78e-b1f0-48e1-a9fc-850a0fb285df","resolution":{"observed_at":"2026-08-11T00:16:23.874792Z","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":"2026-08-11T00:16:23.880027Z","title":"Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.880027Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:0937b167a604a4739ea8015353cd33160086862a55cc4615d4507d8d51f3b98d","observation_id":"f56e34bf-35e4-4d1b-abc5-b1e6c98e4e45","resolution":{"observed_at":"2026-08-11T00:16:23.880027Z","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":"2026-08-11T00:16:24.359141Z","title":"Survey of model-based reinforce- ment learning: Applications on robotics,","venue":null,"work_id":"bb363693-319d-4c13-a68f-687fe3285427","year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.884511Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:33ba348dfbc44aea0a3b23fad614bae29853d18f6a54d573f142d09eba4d4128","observation_id":"8b7a1b97-585c-4403-a955-c9ca5c932d3d","resolution":{"observed_at":"2026-08-11T00:16:24.364116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.343675Z","title":"Online rein- forcement learning control for the personalization of a robotic knee prosthesis,","venue":null,"work_id":"1ce30636-c843-46a4-936c-2171c651cd22","year":2020},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.888893Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:e67fae9aceb5a40f59c2e0edf2c89abfdff5230cde5eb7b012c0bb06035f80ad","observation_id":"5339c8af-fe21-4e11-b91d-bfb4bec52064","resolution":{"observed_at":"2026-08-11T00:16:24.348606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.329022Z","title":"Multitask learning for object localization with deep reinforcement learning,","venue":null,"work_id":"74d0c730-a68a-4e02-922f-46eac79057f5","year":2019},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.893408Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:e1f014d697f3b2410db4484e6914f923b4b7517250fa6987a056a62d09cb8026","observation_id":"38a35f82-5f20-4d49-89a4-fe5136b40840","resolution":{"observed_at":"2026-08-11T00:16:24.333879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.314835Z","title":"Nonzero-sum game rein- forcement learning for performance optimization in large-scale industrial processes,","venue":null,"work_id":"de9fc1b4-1a87-4940-abce-84a488afa447","year":2020},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.897906Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:617c5d5b45f91af4f3e68e1447a1abd5a25832628204eb8a3edb07bcb93b1a36","observation_id":"aee59455-4580-4899-9bc9-b303bbb0aea3","resolution":{"observed_at":"2026-08-11T00:16:24.319281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.300995Z","title":"Neural Architecture Search with Reinforcement Learning,","venue":null,"work_id":"691a4f3e-fdc9-4967-90ec-7a9a4f991aee","year":2016},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.902603Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:0a3c4683a8ed59cca91c7b11faad0c1332d9dd9cced6d8cee07881cf2062c0c0","observation_id":"f9d4505e-ff9a-4a2f-b33b-b3833940fd93","resolution":{"observed_at":"2026-08-11T00:16:24.305262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.287066Z","title":null,"venue":null,"work_id":"4654c3bd-af87-422d-87e8-366795819468","year":1989},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.907878Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:efa42e3c856e87c305a93ded7e4f2e426eacd52254668273171a540742a1f204","observation_id":"98a6976b-4d6f-402b-b7b4-c5f14421a943","resolution":{"observed_at":"2026-08-11T00:16:24.291627Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.690360Z","title":"Spirtes, C","venue":null,"work_id":"affc353d-c042-485d-b7da-10168b2734aa","year":2000},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.912515Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:52d8cec982f35932fa6ff09ce574fa8036c95cf51ec5f45fb450b23937b3392c","observation_id":"a76beb80-dfa6-4983-8d2f-702bdaa43b3d","resolution":{"observed_at":"2026-08-11T00:16:24.694556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.272152Z","title":"A linear non-gaussian acyclic model for causal discovery,","venue":null,"work_id":"fa82712b-abb0-44ae-bbbb-145df784eab4","year":2003},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.917531Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:19bc7ed15a8d631fb0b88bc76db5876a96a1ee6f078a154e3eba64b8a448e94b","observation_id":"13e7c7cf-7f9d-41bd-b1b5-e513c31f0021","resolution":{"observed_at":"2026-08-11T00:16:24.276812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.257922Z","title":"On the Prop- erties of Neural Machine Translation: Encoder-Decoder Approaches,","venue":null,"work_id":"7ae72f66-4746-4c41-aae1-d3f7b5c87c8b","year":2014},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.922413Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:8a9e79b7dab2a8df72481f1e73ce5ca82859b491911de79524bb6b48d8536409","observation_id":"5d600eda-9ff7-4f28-b96d-24d767b2cd0e","resolution":{"observed_at":"2026-08-11T00:16:24.262464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.243531Z","title":"Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond,","venue":null,"work_id":"8e923387-4163-42d2-85b0-1c200e936a12","year":2016},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.927112Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:1d6c85e1a098f4b82017e88c2dd9c92eb87f33b07807871f2444a10c66730920","observation_id":"98d03a7e-f24b-4d1a-87ae-58060d2c65ff","resolution":{"observed_at":"2026-08-11T00:16:24.248028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.228467Z","title":"Function optimization using connectionist reinforcement learning algorithms,","venue":null,"work_id":"8625b156-1365-4955-a289-378234944e60","year":1991},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.931745Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:275d96c40928bc8ab162535e01609210025c6067bd35779332f7502d5b78e681","observation_id":"de8ac5a4-6dd7-4a42-b845-f7f3a4f9eb4f","resolution":{"observed_at":"2026-08-11T00:16:24.233241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.212211Z","title":"Prioritized Experience Replay,","venue":null,"work_id":"e40ad45d-99a6-4b52-8c36-897f31815fa3","year":2015},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.935842Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:8ef2b9fb4c98f36d04fe274777202ff966dc189f9220f88eb72f6b01a244d7d4","observation_id":"d7a64fa6-b5cb-4c63-8a72-3d9c215496fd","resolution":{"observed_at":"2026-08-11T00:16:24.217630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.02553","last_updated":"2020-05-25T16:24:26Z","snapshot_observed_at":"2026-08-11T02:16:51.471401Z","submitted_at":"2018-11-06T18:54:21Z","title":"A Closer Look at Deep Policy Gradients","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.02553","snapshot_observed_at":"2026-08-11T00:16:23.939980Z","title":"Are deep policy gradient algorithms truly policy gradient algorithms?","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.939980Z"},"links":{"cited_paper":"/paper/1811.02553","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:90ae16d46e34a52655d840ec7bfb43e10600cb7728b40a5f35b9ccb88f6ad0a1","observation_id":"02c310d8-ef51-42ea-8c21-7bb9d3055930","resolution":{"observed_at":"2026-08-11T00:16:23.939980Z","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":"2026-08-11T00:16:24.195355Z","title":"Ramsey, M","venue":null,"work_id":"f441d2c8-18c7-4821-86b8-52f13f5bb952","year":2017},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.944847Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:8e4b55b9e5ded4f1dc5e4c9b8d879488b5a6b4e93b29219b070385f7089470f4","observation_id":"b2eb6b1b-3ba7-47a6-9d6d-2b4ae0450792","resolution":{"observed_at":"2026-08-11T00:16:24.200418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1310.1533","last_updated":"2014-12-01T12:31:45Z","snapshot_observed_at":"2026-08-05T01:55:03.450710Z","submitted_at":"2013-10-06T03:12:34Z","title":"CAM: Causal additive models, high-dimensional order search and penalized regression","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1310.1533","snapshot_observed_at":"2026-08-11T00:16:23.949439Z","title":"CAM: causal additive models, high-dimensional order search and penalized regression,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.949439Z"},"links":{"cited_paper":"/paper/1310.1533","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:8d69e1e5f47054a190778afbc037bd35145e323109dbb76e6ae4239ed06a6b35","observation_id":"5ebf8539-b350-4a29-965e-01deff009540","resolution":{"observed_at":"2026-08-11T00:16:23.949439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02226","last_updated":"2020-02-18T14:49:33Z","snapshot_observed_at":"2026-08-07T11:29:29.522039Z","submitted_at":"2019-06-05T18:09:55Z","title":"Gradient-Based Neural DAG Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.02226","snapshot_observed_at":"2026-08-11T00:16:23.954516Z","title":"Gradient- based neural DAG learning,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.954516Z"},"links":{"cited_paper":"/paper/1906.02226","citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:45d1e82fbdd2a5396f157282a6b79a9ebe38729274f8e7351ca0c43f08c5404a","observation_id":"97fad022-e43c-4b5c-8b24-1cbe66d64b81","resolution":{"observed_at":"2026-08-11T00:16:23.954516Z","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":"2026-08-11T00:16:24.179352Z","title":"Causal Protein-Signaling Networks Derived from Multiparam- eter Single-Cell Data,","venue":null,"work_id":"e180f379-5246-4766-a46e-beda5dcbb96b","year":2005},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.959228Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:205ba4774bcbc220ecf1a9dd5e1eb93c509cfc9d5e047fd3d1f53049b272b7fb","observation_id":"8b2f416f-b4b3-42a9-861f-8425f32f40f5","resolution":{"observed_at":"2026-08-11T00:16:24.184311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.163542Z","title":"Syntren: a generator of synthetic gene expression data for design and analysis of structure learning algorithms,","venue":null,"work_id":"34ae2896-9da0-4941-8897-c3dd3be94a49","year":2006},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.963624Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:55e3ef3f5d449a2f55511ab403292c16b9a9b99498c2f09380e97c36321b3e7a","observation_id":"0f88161c-039b-4e44-aea1-4696ba564556","resolution":{"observed_at":"2026-08-11T00:16:24.168558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.147507Z","title":"Truly proximal policy optimization,","venue":null,"work_id":"1b7ac4fc-1bef-4126-bbba-bb716d288ea9","year":2019},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.967896Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:d2533f1007b6bb84d8b569bf456ba4e276a4c9ebc880ecc5070aabe47895f655","observation_id":"24123bbd-aeaa-45af-9ae8-15a5b36f1df0","resolution":{"observed_at":"2026-08-11T00:16:24.153034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T00:16:24.129600Z","title":"A hybrid method for nonlinear equations,","venue":null,"work_id":"32314805-d031-4cc9-8f9a-000b780f3cae","year":1970},"citing_paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T00:16:23.971894Z"},"links":{"citing_paper":"/paper/2412.19578"},"observation_digest":"sha256:629f6982617afefa95a488cc37816c370057c245edcfced62b054600f5b530f4","observation_id":"5991fe42-5bed-484d-80b2-56666ca8adec","resolution":{"observed_at":"2026-08-11T00:16:24.136319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.19578","last_updated":"2024-12-27T10:50:43Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T01:18:10.275276Z","submitted_at":"2024-12-27T10:50:43Z","title":"Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":37},"total_outbound_references":48},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2412.19578."}