{"as_of":"2026-08-04T11:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bf46df294e073d059b296da62a60f11afc94d91a37ab513f26de5ce6b943e8d7","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":"2026-08-04T06:34:03.388597+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":"2026-08-03T03:16:06.492108Z","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":"2026-07-03T18:38:49.031648Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":"2302.14017","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-03T18:38:49.031648Z","title":"Full stack optimization of transformer inference: a survey","venue":null,"work_id":"f9b901e4-6e37-437e-bedf-76c25e40f4e2","year":2023},"citing_paper":{"arxiv_id":"2602.06252","last_updated":"2026-04-04T16:57:05Z","snapshot_observed_at":"2026-07-06T22:44:46.690576Z","submitted_at":"2026-02-05T23:02:23Z","title":"D-Legion: A Scalable Many-Core Architecture for Accelerating Matrix Multiplication in Quantized LLMs","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T06:33:14.766545Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2602.06252"},"observation_digest":"sha256:21a0b985dd1388dd1bea31b5fe339c1b1383cb432c3c3b788bf4d7e55d17aa93","observation_id":"de6ce19a-7c98-411b-843c-8cf7c0e94d6d","resolution":{"observed_at":"2026-05-16T06:37:28.960085Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-08-03T03:16:06.492108Z","title":"W., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.09075","last_updated":"2026-06-03T09:18:46Z","snapshot_observed_at":"2026-08-03T03:16:03.605187Z","submitted_at":"2026-02-09T16:09:51Z","title":"Learning to Remember, Learn, and Forget in Attention-Based Models","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T03:16:06.492108Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2602.09075"},"observation_digest":"sha256:8240000543fa63c3a21ffb3b164a6bb8d5bd0b5dc0b8e006ffe8f32b4b0bea65","observation_id":"8cb40e57-c913-4f11-b89c-d47ac3da4d64","resolution":{"observed_at":"2026-08-03T03:16:06.492108Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":"2302.14017","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-03T18:38:49.031648Z","title":"Full stack optimization of transformer inference: a survey","venue":null,"work_id":"f9b901e4-6e37-437e-bedf-76c25e40f4e2","year":2023},"citing_paper":{"arxiv_id":"2604.09048","last_updated":"2026-04-10T07:15:58Z","snapshot_observed_at":"2026-07-06T22:57:59.555972Z","submitted_at":"2026-04-10T07:15:58Z","title":"Watt Counts: Energy-Aware Benchmark for Sustainable LLM Inference on Heterogeneous GPU Architectures","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T17:33:59.777818Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2604.09048"},"observation_digest":"sha256:3856d81ab310cd907b9c1605dbe55a11786eb9829c825d731232c68ee084f6b2","observation_id":"6c75d491-37a0-43e5-a01f-73441826f58a","resolution":{"observed_at":"2026-05-11T06:36:03.486747Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-12T23:32:59.467653Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2604.09054","last_updated":"2026-06-23T01:22:05Z","snapshot_observed_at":"2026-07-12T23:32:56.608872Z","submitted_at":"2026-04-10T07:27:55Z","title":"HAFM: Hierarchical Autoregressive Foundation Model for Music Accompaniment Generation","version":4},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-12T23:32:59.467653Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2604.09054"},"observation_digest":"sha256:94d63118cce6c3244e5d1e80dddc8d3c56aa2d9e1aca3323fdd883d3a0f071f7","observation_id":"af522d9d-bae7-4c65-94db-fd8fefdb935a","resolution":{"observed_at":"2026-07-12T23:32:59.467653Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":"2302.14017","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-03T18:38:49.031648Z","title":"Full stack optimization of transformer inference: a survey","venue":null,"work_id":"f9b901e4-6e37-437e-bedf-76c25e40f4e2","year":2023},"citing_paper":{"arxiv_id":"2604.11512","last_updated":"2026-04-13T14:16:20Z","snapshot_observed_at":"2026-07-06T22:59:54.573362Z","submitted_at":"2026-04-13T14:16:20Z","title":"EdgeCIM: A Hardware-Software Co-Design for CIM-Based Acceleration of Small Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T15:04:49.793158Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2604.11512"},"observation_digest":"sha256:6c20e4a7784947653d5e5feada7729c116700245d3e07aded7283e409a246c89","observation_id":"26e3db36-ea6b-4493-bfe9-30bd271a7079","resolution":{"observed_at":"2026-05-11T11:16:01.588643Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":"2302.14017","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-03T18:38:49.031648Z","title":"Full stack optimization of transformer inference: a survey","venue":null,"work_id":"f9b901e4-6e37-437e-bedf-76c25e40f4e2","year":2023},"citing_paper":{"arxiv_id":"2604.15944","last_updated":"2026-04-20T08:14:34Z","snapshot_observed_at":"2026-07-06T23:03:21.422544Z","submitted_at":"2026-04-17T11:03:52Z","title":"CIMple: Standard-cell SRAM-based CIM with LUT-based split softmax for attention acceleration","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T07:56:53.425178Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2604.15944"},"observation_digest":"sha256:9d93c69cbc33e56d6276779658800baf1113db98d58784041379da1b169d2279","observation_id":"431c1525-8904-44cc-9e97-8d137d5a0425","resolution":{"observed_at":"2026-05-10T07:57:15.117402Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":"2302.14017","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-03T18:38:49.031648Z","title":"Full stack optimization of transformer inference: a survey","venue":null,"work_id":"f9b901e4-6e37-437e-bedf-76c25e40f4e2","year":2023},"citing_paper":{"arxiv_id":"2606.16106","last_updated":"2026-07-08T00:31:46Z","snapshot_observed_at":"2026-08-03T07:00:25.887446Z","submitted_at":"2026-06-15T01:43:55Z","title":"Edge-Inference Governors Need Memory-Clock State","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T02:44:49.539266Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2606.16106"},"observation_digest":"sha256:6dbc3238a1fc410fa342c80585d74790f7070bfdb711f0babc63360b3d574dda","observation_id":"9e9887d7-95d9-4a33-a239-09e47bd96931","resolution":{"observed_at":"2026-07-03T18:38:49.033705Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.14017","snapshot_observed_at":"2026-07-12T13:55:19.148570Z","title":"Full stack optimization of transformer inference: a survey,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.16106","last_updated":"2026-07-08T00:31:46Z","snapshot_observed_at":"2026-08-03T07:00:25.887446Z","submitted_at":"2026-06-15T01:43:55Z","title":"Edge-Inference Governors Need Memory-Clock State","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-12T13:55:19.148570Z"},"links":{"cited_paper":"/paper/2302.14017","citing_paper":"/paper/2606.16106"},"observation_digest":"sha256:3dba25a9daea4c51ddf8aed199669f37cdaf67703f5d2fd7c9f0aaf4aa0f8dc5","observation_id":"5fd2401b-6fbc-46ee-b85b-96ae1df2ebdc","resolution":{"observed_at":"2026-07-12T13:55:19.148570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2302.14017/citation-record","integrity":"/paper/2302.14017/integrity","json":"/paper/2302.14017/citation-record.json","paper":"/paper/2302.14017"},"outbound":[],"paper":{"arxiv_id":"2302.14017","last_updated":"2023-02-27T18:18:13Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T14:56:23.908982Z","submitted_at":"2023-02-27T18:18:13Z","title":"Full Stack Optimization of Transformer Inference: a Survey"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2302.14017."}