{"as_of":"2026-08-07T16:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b6f0c408f76fbdadf8d6ca19f55236415a45d718e24aa01fe484b378ead5b9c6","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T05:17:05.015451Z","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":"2026-07-03T22:29:00.455930Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-08-03T19:04:28.510867Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.02551","last_updated":"2026-08-05T18:31:31Z","snapshot_observed_at":"2026-08-07T15:15:20.060947Z","submitted_at":"2025-12-02T09:20:15Z","title":"CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T19:04:28.510867Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2512.02551"},"observation_digest":"sha256:3cfd24c59402277a7a85a5639b0e6ddad91bd48cea34558319e9e6bc316d6e0f","observation_id":"88e47590-849a-4654-858c-22b63208049d","resolution":{"observed_at":"2026-08-03T19:04:28.510867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-08-03T08:49:50.385438Z","title":"Swizzleperf: Hardware-aware llms for gpu kernel performance optimization.arXiv preprint arXiv:2508.20258,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.15727","last_updated":"2026-06-06T14:44:09Z","snapshot_observed_at":"2026-08-03T08:49:45.204435Z","submitted_at":"2026-01-22T07:53:52Z","title":"Towards Automated Kernel Generation in the Era of LLMs","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T08:49:50.385438Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2601.15727"},"observation_digest":"sha256:46f6d0e2bcb9cef3a1834d81c7165dfc7b5bda7831a53b0793f2b1e1725cdba1","observation_id":"1bcbc9cb-2ef2-4442-ad32-d721ebd61e73","resolution":{"observed_at":"2026-08-03T08:49:50.385438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":"2508.20258","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-07-03T22:29:00.455930Z","title":"SwizzlePerf: Hardware-aware LLMs for GPU kernel performance optimization","venue":null,"work_id":"da635439-83e2-472b-a7b7-454977ba00a7","year":2025},"citing_paper":{"arxiv_id":"2604.20032","last_updated":"2026-07-15T22:02:45Z","snapshot_observed_at":"2026-08-02T15:49:35.703325Z","submitted_at":"2026-04-21T22:23:55Z","title":"LEO: Tracing GPU Stall Root Causes via Cross-Vendor Backward Slicing","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T00:55:09.017037Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2604.20032"},"observation_digest":"sha256:324071d17f21efae4a4a40b26c4b4d0bad7972475282ad37a3b94300d262544d","observation_id":"86fcc89c-f9cc-45dc-8373-fdd0747458cf","resolution":{"observed_at":"2026-05-10T01:04:50.649360Z","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":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-08-02T15:49:36.610007Z","title":"SwizzlePerf: Hardware-aware LLMs for GPU kernel performance optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.20032","last_updated":"2026-07-15T22:02:45Z","snapshot_observed_at":"2026-08-02T15:49:35.703325Z","submitted_at":"2026-04-21T22:23:55Z","title":"LEO: Tracing GPU Stall Root Causes via Cross-Vendor Backward Slicing","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T15:49:36.610007Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2604.20032"},"observation_digest":"sha256:a1630a5de737a6f8dec3494829dd242a816b7b62a681e82cf9997ce461254be1","observation_id":"59802901-4e8e-49ce-8369-9e723d36cdee","resolution":{"observed_at":"2026-08-02T15:49:36.610007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":"2508.20258","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-07-03T22:29:00.455930Z","title":"SwizzlePerf: Hardware-aware LLMs for GPU kernel performance optimization","venue":null,"work_id":"da635439-83e2-472b-a7b7-454977ba00a7","year":2025},"citing_paper":{"arxiv_id":"2605.30359","last_updated":"2026-08-03T01:31:45Z","snapshot_observed_at":"2026-08-06T23:24:42.531300Z","submitted_at":"2026-05-08T03:41:54Z","title":"Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T23:33:47.477482Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2605.30359"},"observation_digest":"sha256:4151266699b5d5053d57aa1aeec263f86448122d8c0a8a305a5b500dd7690e8b","observation_id":"0670648b-7238-4aa5-936d-26be8e3c7ff1","resolution":{"observed_at":"2026-06-30T23:35:07.141292Z","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":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-08-04T05:17:05.015451Z","title":"Swizzleperf: Hardware-aware llms for gpu kernel performance optimization.arXiv preprint arXiv:2508.20258, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.30359","last_updated":"2026-08-03T01:31:45Z","snapshot_observed_at":"2026-08-06T23:24:42.531300Z","submitted_at":"2026-05-08T03:41:54Z","title":"Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T05:17:05.015451Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2605.30359"},"observation_digest":"sha256:0f33ee41b27060536a55a70d7478b1df84176f9df6d86a63b103d0135918e763","observation_id":"460e180a-3037-4469-8328-8c697cb0b7bf","resolution":{"observed_at":"2026-08-04T05:17:05.015451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":"2508.20258","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-07-03T22:29:00.455930Z","title":"SwizzlePerf: Hardware-aware LLMs for GPU kernel performance optimization","venue":null,"work_id":"da635439-83e2-472b-a7b7-454977ba00a7","year":2025},"citing_paper":{"arxiv_id":"2606.17518","last_updated":"2026-06-16T04:54:23Z","snapshot_observed_at":"2026-07-06T23:53:07.149182Z","submitted_at":"2026-06-16T04:54:23Z","title":"SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-26T23:35:32.175768Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2606.17518"},"observation_digest":"sha256:e0fbf23e210ac93d1352e674ed7a97a5149e5c38c8dd8cf6d8f5af9433150240","observation_id":"4a565637-34fa-4324-8f73-ba9102e76de5","resolution":{"observed_at":"2026-07-03T22:29:00.457665Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2508.20258","last_updated":"2025-08-27T20:30:43Z","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20258","snapshot_observed_at":"2026-08-02T13:46:47.513187Z","title":"Swizzleperf: Hardware-aware llms for gpu kernel performance optimization.arXiv preprint arXiv:2508.20258, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20466","last_updated":"2026-05-19T05:38:39Z","snapshot_observed_at":"2026-08-06T15:33:05.072901Z","submitted_at":"2026-05-19T05:38:39Z","title":"JAXBench: Benchmarking Autonomous TPU Kernel Optimization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T13:46:47.513187Z"},"links":{"cited_paper":"/paper/2508.20258","citing_paper":"/paper/2607.20466"},"observation_digest":"sha256:615cc0208cde874b4de0c58e2dedb1d6564916104403ab1b218b045ec2845476","observation_id":"030a03f7-669e-4e8b-b5a6-e982ee3547f3","resolution":{"observed_at":"2026-08-02T13:46:47.513187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.20258/citation-record","integrity":"/paper/2508.20258/integrity","json":"/paper/2508.20258/citation-record.json","paper":"/paper/2508.20258"},"outbound":[],"paper":{"arxiv_id":"2508.20258","last_updated":"2025-08-27T20:30:43Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-05T15:10:38.934719Z","submitted_at":"2025-08-27T20:30:43Z","title":"SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization"},"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 8 inbound Pith citation observations for arXiv:2508.20258."}