{"as_of":"2026-08-08T01:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f8da231a63e98603849df7cd2ab62cb1a190c5f2146dc2331b01e2a657b0963b","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:12:13.860474Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.00315/citation-record","integrity":"/paper/2506.00315/integrity","json":"/paper/2506.00315/citation-record.json","paper":"/paper/2506.00315"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:11.795785Z","title":"URL: \" 'urlintro :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:11.795785Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:f61cf46642954ca3dc62d0fd220dc05db81b7b8d64c5a57ed3aaffb7541da1ac","observation_id":"dfa13584-b642-4081-9bfe-06fd4741a4e2","resolution":{"observed_at":"2026-08-07T12:12:11.795785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:11.984343Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:11.984343Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:3b8bdf4c9d7a99d952f0f98a56746c52be6cce1aecfb35f4584bf3063cbb0793","observation_id":"aa8e7e77-3884-42f9-884b-785c72b9add9","resolution":{"observed_at":"2026-08-07T12:12:11.984343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:15.628964Z","title":"Gholami, S","venue":null,"work_id":"f00cfa9b-e251-4e20-9f2f-1d1df9e3d0fb","year":2022},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.138487Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:30a9c3beae395941d8f0b2c3eabe1dd17424b3b088575953f06e00cbb33a2290","observation_id":"f0d88cec-fa0b-4851-8e93-3958b0ac43da","resolution":{"observed_at":"2026-08-07T12:12:15.715112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"1806.08342","last_updated":"2018-06-21T17:32:46Z","snapshot_observed_at":"2026-07-06T06:46:08.396066Z","submitted_at":"2018-06-21T17:32:46Z","title":"Quantizing deep convolutional networks for efficient inference: A whitepaper","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.08342","snapshot_observed_at":"2026-08-07T12:12:12.294927Z","title":"Krishnamoorthi, ``Quantizing deep convolutional networks for efficient inference: A whitepaper,'' arXiv preprint arXiv:1806.08342 , 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.294927Z"},"links":{"cited_paper":"/paper/1806.08342","citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:a5a71549f512715be1631ea4361c1eb1a6a5d6a8dc3d1c86830f36e451fb9009","observation_id":"2fb3bb1f-2f05-4e91-8729-55104da8e4c7","resolution":{"observed_at":"2026-08-07T12:12:12.294927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.09602","last_updated":"2020-04-20T19:59:22Z","snapshot_observed_at":"2026-07-06T09:13:49.452689Z","submitted_at":"2020-04-20T19:59:22Z","title":"Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.09602","snapshot_observed_at":"2026-08-07T12:12:12.442972Z","title":null,"venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.442972Z"},"links":{"cited_paper":"/paper/2004.09602","citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:6df92e4fcba0e854f8f6ce8250ea8d88d41544b2dcffff44d44056c20787a00b","observation_id":"ba2b57fa-d859-4d6e-8514-009769030acd","resolution":{"observed_at":"2026-08-07T12:12:12.442972Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.05025","last_updated":"2022-03-09T19:57:14Z","snapshot_observed_at":"2026-07-06T12:46:12.270140Z","submitted_at":"2022-03-09T19:57:14Z","title":"Power-of-Two Quantization for Low Bitwidth and Hardware Compliant Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.05025","snapshot_observed_at":"2026-08-07T12:12:12.610791Z","title":"Przewlocka-Rus, S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.610791Z"},"links":{"cited_paper":"/paper/2203.05025","citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:da312e5d46026f3ceca10aa3cb25dc96d81621fb51de55642b4a0e6a6adefb6f","observation_id":"89ada610-963c-498f-8888-7b66aafe082e","resolution":{"observed_at":"2026-08-07T12:12:12.610791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:15.429023Z","title":"McDanel, S","venue":null,"work_id":"85d0fb88-75a6-4bdd-93b5-8e00ec388bc1","year":2019},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.768176Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:0808bc44bd68667d5aea9034cd3d33d7a8ae4d3119287b90e57d5c62832e3d45","observation_id":"cc2ab939-ce95-4e04-a2b0-855369caea44","resolution":{"observed_at":"2026-08-07T12:12:15.523982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:15.242646Z","title":null,"venue":null,"work_id":"0c7522db-ed26-47a2-9e48-a8fce290ea13","year":2025},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:12.882831Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:417f2c2880134c6e4ccb5df04ab6915b62f252235cc791094bbbeead82b02f1c","observation_id":"c40878ea-f7f2-4baf-880c-a7f4a5c2d165","resolution":{"observed_at":"2026-08-07T12:12:15.313758Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:15.066350Z","title":null,"venue":null,"work_id":"ad4f69e8-7fb0-4f28-9ef2-62ef201b5fc5","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.079987Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:0e311a8964e384e98204e4699be27006d295e70e54f616b654f1ee6578376fe7","observation_id":"fdee5999-8918-4e73-831a-5f825143e144","resolution":{"observed_at":"2026-08-07T12:12:15.138736Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:14.900692Z","title":"openwebtext","venue":null,"work_id":"6ceafae3-a71f-415c-b813-93dff68ffeb2","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.200868Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:7ad335301367f74910a7aac36d1b175bc7c5c042b9f3e4064fe1973b9a979c0b","observation_id":"6938070e-431e-4f46-99dc-dd494f620bd9","resolution":{"observed_at":"2026-08-07T12:12:14.985932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:14.741233Z","title":null,"venue":null,"work_id":"ab94d32a-35e1-443a-b2d4-4b8d55bb5078","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.361912Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:de718ddd85b106bdfbbd89dfe09b82211d4e4fad9fd542a6a2a23f7ccedf7fd8","observation_id":"76d5dee7-18b5-4946-8cab-7a9780d8489d","resolution":{"observed_at":"2026-08-07T12:12:14.812370Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:14.545587Z","title":null,"venue":null,"work_id":"37bc6747-65dd-4c16-9978-1a6f0d5c6971","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.557825Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:7509cc2ca83c9b18be6e5a2c06337c69a89f9ccfa2eea655d87926e7915f9611","observation_id":"e57126bb-9715-4386-bbff-59ced2198bba","resolution":{"observed_at":"2026-08-07T12:12:14.640189Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:14.338954Z","title":null,"venue":null,"work_id":"a62c2ecf-c9ed-4574-b59e-9599bb5fc708","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.737986Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:3af4896b39610669dad626a82a5a2cfe2d69f5f72d87e80152fed415a041ed85","observation_id":"f3b7fe43-607c-43a8-a870-18aa21d1a4b2","resolution":{"observed_at":"2026-08-07T12:12:14.406499Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:12:14.070061Z","title":null,"venue":null,"work_id":"570671cc-9abc-46dc-a878-a09852a6b647","year":null},"citing_paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T12:12:13.860474Z"},"links":{"citing_paper":"/paper/2506.00315"},"observation_digest":"sha256:8c96c8f4e12e3a87eee5992b138177b4a21adedbdf1b4419c8e06f79e03919e2","observation_id":"bb795ccd-2192-425c-b55c-222241aea932","resolution":{"observed_at":"2026-08-07T12:12:14.224957Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}}],"paper":{"arxiv_id":"2506.00315","last_updated":"2025-05-31T00:01:25Z","latest_version":1,"primary_category":"eess.SP","snapshot_observed_at":"2026-08-07T12:05:28.270904Z","submitted_at":"2025-05-31T00:01:25Z","title":"Power-of-Two (PoT) Weights in Large Language Models (LLMs)"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":10,"verified_exact":0,"verified_fuzzy":3},"total_outbound_references":14},"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 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.00315."}