{"as_of":"2026-08-05T07:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f9c281bc95e398bbcc5bda0d53a7cac3bbd1ee8b9f4becdfd5a121dbacfb56ba","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T11:31:30.707206Z","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":"2026-07-01T19:16:00.843940Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-08-04T11:31:30.707206Z","title":"Dopq- vit: Towards distribution-friendly and outlier-aware post- training quantization for vision transformers.arXiv preprint arXiv:2408.03291, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.04547","last_updated":"2026-07-08T06:28:12Z","snapshot_observed_at":"2026-08-04T11:31:24.487749Z","submitted_at":"2025-10-06T07:27:46Z","title":"Activation Quantization of Vision Encoders Needs Prefixing Registers","version":5},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T11:31:30.707206Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2510.04547"},"observation_digest":"sha256:bf8d453bdeba88393e3c8e425369c483652d77b7e0af0f287d1dc719d4c4a0b1","observation_id":"7855009e-1a87-4611-85ad-8c52484a4743","resolution":{"observed_at":"2026-08-04T11:31:30.707206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":"2408.03291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-29T01:24:21.058523Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transform- ers","venue":null,"work_id":"c33f205d-0971-497b-b20d-d5d8430a800d","year":2024},"citing_paper":{"arxiv_id":"2602.20309","last_updated":"2026-04-06T23:32:59Z","snapshot_observed_at":"2026-08-02T13:10:10.837199Z","submitted_at":"2026-02-23T19:55:54Z","title":"QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models","version":4},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-15T20:20:10.435886Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2602.20309"},"observation_digest":"sha256:d2baf7b951a0441f47ad9feab64397f9826fe6072e47847911f251025982cf94","observation_id":"af056179-2fd3-4ad3-8b8e-110bfee488c9","resolution":{"observed_at":"2026-07-29T01:24:21.058523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":"2408.03291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-29T01:24:21.058523Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transform- ers","venue":null,"work_id":"c33f205d-0971-497b-b20d-d5d8430a800d","year":2024},"citing_paper":{"arxiv_id":"2604.17789","last_updated":"2026-04-21T07:37:48Z","snapshot_observed_at":"2026-07-06T23:04:50.935335Z","submitted_at":"2026-04-20T04:27:28Z","title":"DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T05:59:23.738476Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2604.17789"},"observation_digest":"sha256:ab23f8436745ae5e869d3ed097e43cd3e983b7e300a4966899e31d6749f7035b","observation_id":"85f03042-ff6d-48fa-9dfc-22fca5e08c52","resolution":{"observed_at":"2026-07-29T01:24:21.058523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":"2408.03291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-29T01:24:21.058523Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transform- ers","venue":null,"work_id":"c33f205d-0971-497b-b20d-d5d8430a800d","year":2024},"citing_paper":{"arxiv_id":"2605.01330","last_updated":"2026-05-02T08:49:51Z","snapshot_observed_at":"2026-07-06T23:14:33.653260Z","submitted_at":"2026-05-02T08:49:51Z","title":"Colinearity Decay: Training Quantization-Friendly ViTs with Outlier Decay","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-09T14:24:54.946996Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2605.01330"},"observation_digest":"sha256:e8ea532e2269ed5d37c3ea3b897ebb0bf79c85b618fa9f87e3b803e32be4d5f4","observation_id":"ef58d8d2-0574-4feb-b14f-992515dc4f89","resolution":{"observed_at":"2026-07-29T01:24:21.058523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":"2408.03291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-29T01:24:21.058523Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transform- ers","venue":null,"work_id":"c33f205d-0971-497b-b20d-d5d8430a800d","year":2024},"citing_paper":{"arxiv_id":"2605.16423","last_updated":"2026-05-14T14:55:46Z","snapshot_observed_at":"2026-07-06T23:27:34.514541Z","submitted_at":"2026-05-14T14:55:46Z","title":"Nonlinear Bipolar Compensation: Handling Outliers in Post-Training Quantization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-20T20:55:10.360775Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2605.16423"},"observation_digest":"sha256:70c80298bcefee7f38bf2154b339afb5b798fffcff4777956a6893395ce5b6eb","observation_id":"cb9a457f-556e-478c-8d76-df93d18d61b4","resolution":{"observed_at":"2026-07-29T01:24:21.058523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":"2408.03291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-29T01:24:21.058523Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transform- ers","venue":null,"work_id":"c33f205d-0971-497b-b20d-d5d8430a800d","year":2024},"citing_paper":{"arxiv_id":"2605.31124","last_updated":"2026-05-29T10:32:52Z","snapshot_observed_at":"2026-08-01T21:08:45.055864Z","submitted_at":"2026-05-29T10:32:52Z","title":"QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-28T22:54:52.597232Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2605.31124"},"observation_digest":"sha256:176728d7b25f284f0563e6492289d3f54ff1c81a2aadd122049e843daab384bf","observation_id":"e52cee3b-6524-40de-8718-cfff6cecee06","resolution":{"observed_at":"2026-07-29T01:24:21.058523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03291","snapshot_observed_at":"2026-07-31T02:57:29.309270Z","title":"Dopq-vit: Towards distribution-friendly and outlier-aware post-training quantization for vision transformers.ArXiv, abs/2408.03291,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.28589","last_updated":"2026-07-30T17:43:36Z","snapshot_observed_at":"2026-08-03T00:12:32.913568Z","submitted_at":"2026-07-30T17:43:36Z","title":"MixFrag: Fragility-Guided Mixed-Precision Post-Training Quantization for Vision Transformers","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-31T02:57:29.309270Z"},"links":{"cited_paper":"/paper/2408.03291","citing_paper":"/paper/2607.28589"},"observation_digest":"sha256:99cb480849cd9e4551cf3db0c10bba893edca44a4cdccff68e1e23a79d6d6f63","observation_id":"26c03923-3228-4e00-b875-e61d40d8f1da","resolution":{"observed_at":"2026-07-31T02:57:29.309270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2408.03291/citation-record","integrity":"/paper/2408.03291/integrity","json":"/paper/2408.03291/citation-record.json","paper":"/paper/2408.03291"},"outbound":[],"paper":{"arxiv_id":"2408.03291","last_updated":"2026-07-28T09:18:13Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-31T23:52:44.107316Z","submitted_at":"2024-08-06T16:40:04Z","title":"DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.03291."}