{"as_of":"2026-08-07T12:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c68ef970dd7c57698613ce28dc065f17afefd8f413c1aa456f3671569514529a","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:54:51.776424Z","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":"2026-07-03T21:08:58.138772Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-08-07T00:54:51.776424Z","title":"Quamba: A post-training quantization recipe for selective state space models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12480","last_updated":"2025-06-14T12:43:47Z","snapshot_observed_at":"2026-08-07T00:46:20.012471Z","submitted_at":"2025-06-14T12:43:47Z","title":"Quantizing Small-Scale State-Space Models for Edge AI","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:54:51.776424Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2506.12480"},"observation_digest":"sha256:0ce761b72621fee113319a667c6c4bc4ad40d400ab5fd0745eec1b6bc7d58a43","observation_id":"4f9dc540-850d-4776-9e5c-fda8eb03a6e2","resolution":{"observed_at":"2026-08-07T00:54:51.776424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-08-06T19:16:24.272098Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06079","last_updated":"2025-07-08T15:19:14Z","snapshot_observed_at":"2026-08-06T19:09:18.164681Z","submitted_at":"2025-07-08T15:19:14Z","title":"QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T19:16:24.272098Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2507.06079"},"observation_digest":"sha256:d607b8a2d663f839cafee686219d9b01f6fd514c277f03efe037aa9e62a03e43","observation_id":"1a2ae952-0c62-4fbf-8c97-ef6486a77be3","resolution":{"observed_at":"2026-08-06T19:16:24.272098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-08-05T20:34:25.774194Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.10370","last_updated":"2025-08-14T06:08:05Z","snapshot_observed_at":"2026-08-07T09:46:53.471270Z","submitted_at":"2025-08-14T06:08:05Z","title":"eMamba: Efficient Acceleration Framework for Mamba Models in Edge Computing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T20:34:25.774194Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2508.10370"},"observation_digest":"sha256:7acf69643091a7cd00279056d6ffefc32acb77ce63e65f768d2aeec464968726","observation_id":"c6ced7d0-e01f-4d1d-bb4b-4e3632aff35d","resolution":{"observed_at":"2026-08-05T20:34:25.774194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":"2410.13229","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-07-03T21:08:58.138772Z","title":"Quamba: A post-training quantization recipe for selective state space models.arXiv preprint arXiv:2410.13229","venue":null,"work_id":"e68bca11-bfc4-4a23-bc68-7d4949b038ee","year":2024},"citing_paper":{"arxiv_id":"2604.10597","last_updated":"2026-05-02T01:07:43Z","snapshot_observed_at":"2026-07-06T22:59:09.778842Z","submitted_at":"2026-04-12T12:07:48Z","title":"COREY: Entropy-Guided Runtime Chunk Scheduling for Selective Scan Kernels","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T15:10:02.445509Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2604.10597"},"observation_digest":"sha256:15e59aa71ee7f249763698dd2826fb05d5cc9d6cea76ccb144a688d913521d17","observation_id":"d20110d7-33b5-4b6b-a17f-4a294c61d121","resolution":{"observed_at":"2026-05-11T11:06:03.476969Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":"2410.13229","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-07-03T21:08:58.138772Z","title":"Quamba: A post-training quantization recipe for selective state space models.arXiv preprint arXiv:2410.13229","venue":null,"work_id":"e68bca11-bfc4-4a23-bc68-7d4949b038ee","year":2024},"citing_paper":{"arxiv_id":"2606.18114","last_updated":"2026-06-16T16:18:21Z","snapshot_observed_at":"2026-08-07T03:30:32.913413Z","submitted_at":"2026-06-16T16:18:21Z","title":"Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T00:55:02.737906Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2606.18114"},"observation_digest":"sha256:7c720ca48c07150954b2206810633fce43a484a2ea3f9e2e9b695d01568ac126","observation_id":"6ef94bb7-6a23-4f8f-8e7a-76502c651650","resolution":{"observed_at":"2026-07-03T21:08:58.140324Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13229","snapshot_observed_at":"2026-08-06T23:25:10.355759Z","title":"Quamba: A post-training quantization recipe for selective state space models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.04488","last_updated":"2026-08-05T06:20:57Z","snapshot_observed_at":"2026-08-07T11:42:53.328398Z","submitted_at":"2026-08-05T06:20:57Z","title":"Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T23:25:10.355759Z"},"links":{"cited_paper":"/paper/2410.13229","citing_paper":"/paper/2608.04488"},"observation_digest":"sha256:2064421b50094f062786a0a2300faf917f4daaa6ef63df0530965f757990733c","observation_id":"200549dc-d921-4109-8bf5-e377a06fe0fa","resolution":{"observed_at":"2026-08-06T23:25:10.355759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.13229/citation-record","integrity":"/paper/2410.13229/integrity","json":"/paper/2410.13229/citation-record.json","paper":"/paper/2410.13229"},"outbound":[],"paper":{"arxiv_id":"2410.13229","last_updated":"2024-12-07T07:27:00Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T22:39:19.035342Z","submitted_at":"2024-10-17T05:32:33Z","title":"Quamba: A Post-Training Quantization Recipe for Selective State Space Models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.13229."}