{"as_of":"2026-08-11T15:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c802723ff41c03720cbc0c4a92bb6ce014ce43d2f7407f29a01a2917538cdd2","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-13T10:46:25.335756Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-01T13:05:45.530664Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2504.18743","last_updated":"2026-04-05T13:54:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-25T23:41:14Z","title":"From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-22T17:34:49.191496Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2504.18743"},"observation_digest":"sha256:f85238673d58e49b45b641524a1d320c013db4d2fed2ff13ba2493cb4ed5d931","observation_id":"7059be44-e7d7-47d7-b37c-ac070274758a","resolution":{"observed_at":"2026-05-22T17:35:00.842255Z","resolver_source":"arxiv_id","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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2509.18964","last_updated":"2026-04-20T11:35:29Z","snapshot_observed_at":"2026-07-06T22:30:31.933240Z","submitted_at":"2025-09-23T13:16:14Z","title":"Central Limit Theorems for Asynchronous Averaged Q-Learning","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-18T14:55:49.034505Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2509.18964"},"observation_digest":"sha256:5a740b454b01b03f15041d584be4b3e49bbf61a84e780287248794eafa94d1ab","observation_id":"ea9749e5-69e4-4847-9ef0-ed364951065e","resolution":{"observed_at":"2026-05-18T14:56:30.395591Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2510.16132","last_updated":"2026-04-03T19:00:32Z","snapshot_observed_at":"2026-07-06T22:32:57.286856Z","submitted_at":"2025-10-17T18:19:00Z","title":"A Minimal-Assumption Analysis of Q-Learning with Time-Varying Policies","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-18T05:47:47.782246Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2510.16132"},"observation_digest":"sha256:01d4d8d167da6ba584d3cfad770557820197c3aed61dcccb27a106fba7355fc6","observation_id":"97155cf2-5cfc-4627-92be-fd8d4a93244e","resolution":{"observed_at":"2026-05-18T05:50:57.154573Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2601.08184","last_updated":"2026-04-20T17:00:57Z","snapshot_observed_at":"2026-07-06T22:41:33.987055Z","submitted_at":"2026-01-13T03:25:24Z","title":"Wasserstein-p Central Limit Theorem Rates: From Local Dependence to Markov Chains","version":3},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-16T15:21:02.872523Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2601.08184"},"observation_digest":"sha256:50f9e734b72204a96648aa048d42a434012c790dc669fa859519089d77106f8b","observation_id":"138a38e0-9a1b-42ef-8472-7956e3581bb7","resolution":{"observed_at":"2026-05-16T15:23:02.079774Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-13T10:46:25.335756Z","title":"Zhang and Q","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.04218","last_updated":"2026-04-05T18:31:51Z","snapshot_observed_at":"2026-07-13T10:46:19.431432Z","submitted_at":"2026-04-05T18:31:51Z","title":"Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-07-13T10:46:25.335756Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2604.04218"},"observation_digest":"sha256:bed78a03a304a978b712e79e0c04a6c086ee1b6646ae398a39e32b8bfbf89713","observation_id":"82258d0c-a47d-4238-99e1-9b2d32e949e7","resolution":{"observed_at":"2026-07-13T10:46:25.335756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2604.10373","last_updated":"2026-04-11T22:59:26Z","snapshot_observed_at":"2026-07-06T22:59:01.129724Z","submitted_at":"2026-04-11T22:59:26Z","title":"Shuffling the Data, Stretching the Step-size: Sharper Bias in constant step-size SGD","version":1},"reference_index":141,"source":"arxiv_source","source_observed_at":"2026-05-10T15:13:59.395799Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2604.10373"},"observation_digest":"sha256:bc42574055d09da2afae968f3dd0a33fc42d058118e476645b9959715f83e760","observation_id":"93b7c764-836c-4c16-80d8-d05af1def6a2","resolution":{"observed_at":"2026-05-11T11:01:03.712977Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2604.13378","last_updated":"2026-04-15T01:02:42Z","snapshot_observed_at":"2026-07-06T23:01:23.771347Z","submitted_at":"2026-04-15T01:02:42Z","title":"Revisiting the Constant Stepsize Stochastic Approximation with Decision-Dependent Markovian Noise","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-05-10T13:45:04.730863Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2604.13378"},"observation_digest":"sha256:c7fa264a5b76d3285e1c2251d494fdba9789832cc8c70dbb4590092034b51006","observation_id":"7d748d63-82fb-49f6-8a9b-afccb39e68aa","resolution":{"observed_at":"2026-05-10T13:45:27.427927Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2604.17302","last_updated":"2026-04-19T07:36:48Z","snapshot_observed_at":"2026-07-06T23:04:28.260463Z","submitted_at":"2026-04-19T07:36:48Z","title":"Elephant random walk with attributed steps and extractions of random sizes","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-10T06:09:29.594763Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2604.17302"},"observation_digest":"sha256:36273e324ae87e8527a91750208b9882c5f05856c52f0f13b19c6f4395f06df2","observation_id":"cca55c52-38fc-4b2f-8279-dea5dc13086f","resolution":{"observed_at":"2026-05-10T06:11:20.120298Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2605.19629","last_updated":"2026-05-19T10:08:01Z","snapshot_observed_at":"2026-07-06T23:30:21.283826Z","submitted_at":"2026-05-19T10:08:01Z","title":"Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-05-20T02:10:02.167114Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2605.19629"},"observation_digest":"sha256:ca86b1cf763257a13f5577a3f5552f31db2cbfe2510f24595495d25ca6a2bb74","observation_id":"a9ac911b-bb77-45f5-85b8-1191a1b91f4c","resolution":{"observed_at":"2026-05-20T02:12:58.456482Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2401.13884","last_updated":"2024-01-25T02:01:53Z","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation","version":1},"cited_work":{"arxiv_id":"2401.13884","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13884","snapshot_observed_at":"2026-07-01T13:05:45.530664Z","title":"and Xie, Q","venue":null,"work_id":"a69febfa-1f08-4340-9aa4-d2675e77b066","year":2024},"citing_paper":{"arxiv_id":"2606.30930","last_updated":"2026-06-29T21:32:58Z","snapshot_observed_at":"2026-08-06T09:55:08.155994Z","submitted_at":"2026-06-29T21:32:58Z","title":"SGD at the Edge of Stability: Stochastic Stabilization with Large Learning Rates","version":1},"reference_index":221,"source":"arxiv_source","source_observed_at":"2026-07-01T01:05:17.842447Z"},"links":{"cited_paper":"/paper/2401.13884","citing_paper":"/paper/2606.30930"},"observation_digest":"sha256:7a49823194984bc7f861c3f867aeab9b06c4f65ad1c870ff20c7c002e15c3b32","observation_id":"429ac6e2-176d-4cb7-80e2-78b514eb8ed3","resolution":{"observed_at":"2026-07-01T13:05:45.532477Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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/2401.13884/citation-record","integrity":"/paper/2401.13884/integrity","json":"/paper/2401.13884/citation-record.json","paper":"/paper/2401.13884"},"outbound":[],"paper":{"arxiv_id":"2401.13884","last_updated":"2024-01-25T02:01:53Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-07-06T17:20:11.913242Z","submitted_at":"2024-01-25T02:01:53Z","title":"Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2401.13884."}