{"as_of":"2026-08-23T23:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8cfe723af0d65ff14b53387ad2df44fb5423d4fa8644cd189a7a16dc4e0cf44c","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T15:37:48.987092Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2605.30612/citation-record","integrity":"/paper/2605.30612/integrity","json":"/paper/2605.30612/citation-record.json","paper":"/paper/2605.30612"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T15:37:48.987092Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:4de1ef37ab0246373b2bb5b0a6664e169706a1a1fcce159c74b17c79b98e1ff3","observation_id":"a31358f2-9ca1-4fce-8e76-a0b3a5f0e376","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-07-12T15:37:48.987092Z","title":"Mysore, B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:d9673677fb66745b8b6f25552dd11ed9361ae47c179845f67fad29be2ada1ec8","observation_id":"8d5e0044-29c1-48c8-9873-5663fa077a2a","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:81e859a84f645dd5307d4c5eb3b10dd567b7c8e478020dc5b3302eccbc7b5eb7","observation_id":"df8d6344-bb9a-49a6-8a80-852010f8d53f","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Ho and S","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:59a103c7d52e1a3c6904e8473ae7b4b5fb492f3f7cb5f260dd7906434d238fd8","observation_id":"48d4365d-6140-4eaa-a5ab-7956c89ce438","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.05905","last_updated":"2019-01-29T12:10:47Z","snapshot_observed_at":"2026-08-17T07:51:41.384508Z","submitted_at":"2018-12-13T04:44:29Z","title":"Soft Actor-Critic Algorithms and Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.05905","snapshot_observed_at":"2026-07-12T15:37:48.987092Z","title":"Haarnoja, A","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"cited_paper":"/paper/1812.05905","citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:3a1539549aa44b90dd3da3f347035bf91c8fb42c126cf76a195e93081ea357a9","observation_id":"5add10f4-062f-4cc2-a46e-fcc1e5c470c2","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Savitzky and M","venue":null,"work_id":null,"year":1964},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:f33d5012901f5a0995cfc9241ba169f9fd3d367471d1e02346ce4e9a665c548f","observation_id":"b0c2bede-630b-411e-be84-882ca57928b4","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Hinton, O","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:7a859558efe1b2338dd300ccb91c5d43040f78cc3f65bb7bd3e3d077afa284ec","observation_id":"e18adca3-e227-4e83-99a3-78324ed871fa","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Stooke, J","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:ee8e756f1efc70188bd61ec29c8632a88198ef12f4c6f1d8d989d59ae0fdb95f","observation_id":"7ef19cda-f8a8-4e60-86d6-a8ad43ee98ba","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:3bd031be5e1ac09e0dc90aaaec258b675feb72ffa39db5161a68c681d4c93b25","observation_id":"0c91ebb2-dc97-4433-aeb4-ba38b2f64263","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Michel, ``Cyberbotics Ltd.\\ Webots: Professional Mobile Robot Simulation,'' Journal of Advanced Robotics Systems, vol","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:27bb24383c4a913040d4629ac3defaf204f2f96ffc1240ac510469e56a826bfb","observation_id":"2a383af9-d65c-4655-a632-1fdf3230d4f9","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Hausknecht and P","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:7e12c98413d410c7daa71790481d7c88f377ac04a6a46831402d6246569502e7","observation_id":"70606d85-1d91-43a4-bc36-8254723fb9ab","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Andrychowicz et al., ``Learning Dexterous In-Hand Manipulation,'' IJRR, vol","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:b372e5a7e78fa762006dac33f9cf8d0fa009901d9321c845b87d4451c7c77d97","observation_id":"ffde2fa7-bb0b-4058-b534-8830a9aea666","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","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":"2026-07-12T15:37:48.987092Z","title":"Siciliano, L","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-12T15:37:48.987092Z"},"links":{"citing_paper":"/paper/2605.30612"},"observation_digest":"sha256:80756fbeec4f2601dacacf43fa6dbda99fd52a5f0e2b0a0ac0881429df510ca3","observation_id":"1e290a19-51d9-48d9-b8d5-f1e021f89275","resolution":{"observed_at":"2026-07-12T15:37:48.987092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2605.30612","last_updated":"2026-07-08T22:55:05Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-18T06:32:27.032426Z","submitted_at":"2026-05-28T22:05:08Z","title":"ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":13},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2605.30612."}