{"as_of":"2026-08-07T12:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6215be8c999def8c0d6efa31ae41488b3cec44c2cb4317b4afcbe66e3f409cd1","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:34:04.396377Z","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":"2026-07-02T11:26:54.353732Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-08-07T10:34:04.396377Z","title":"Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05007","last_updated":"2025-06-05T13:17:50Z","snapshot_observed_at":"2026-08-07T10:26:04.432370Z","submitted_at":"2025-06-05T13:17:50Z","title":"QiMeng: Fully Automated Hardware and Software Design for Processor Chip","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T10:34:04.396377Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2506.05007"},"observation_digest":"sha256:02ea090d5a73260cff6be47c0faa23bc4301c037b0968b9b57f11251767106da","observation_id":"267bfea6-d13c-41b0-bed5-3bfdef747ef2","resolution":{"observed_at":"2026-08-07T10:34:04.396377Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-08-06T15:51:34.431027Z","title":"Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.14776","last_updated":"2025-07-20T00:28:55Z","snapshot_observed_at":"2026-08-06T17:02:06.602812Z","submitted_at":"2025-07-20T00:28:55Z","title":"VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:51:34.431027Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2507.14776"},"observation_digest":"sha256:bd64e6b6bbffc0e489c5e4224f8b0ce90d2a1e86458f98842e183e5e3ef5f817","observation_id":"ed1710f7-c9ff-4636-8fab-3ddaa7089255","resolution":{"observed_at":"2026-08-06T15:51:34.431027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-08-06T15:19:52.253221Z","title":"Rtlcoder: Outper- forming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16200","last_updated":"2025-07-22T03:29:23Z","snapshot_observed_at":"2026-08-06T15:13:16.621566Z","submitted_at":"2025-07-22T03:29:23Z","title":"RealBench: Benchmarking Verilog Generation Models with Real-World IP Designs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:19:52.253221Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2507.16200"},"observation_digest":"sha256:c7fff4cea40b47d4d10036ed06b1057117b3c44454f230984a3012fe6525f08e","observation_id":"84c0b0b9-c2a6-4899-9341-9ccb86a0d787","resolution":{"observed_at":"2026-08-06T15:19:52.253221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-08-05T16:00:39.439485Z","title":"Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.00071","last_updated":"2025-08-26T15:11:10Z","snapshot_observed_at":"2026-08-05T16:00:38.949929Z","submitted_at":"2025-08-26T15:11:10Z","title":"SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T16:00:39.439485Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2509.00071"},"observation_digest":"sha256:837bf8c48d2e00bb34d03f76494da42a6335a0ee07d4943644b6e958da26fd20","observation_id":"0fe74f83-553e-4f91-a8cb-5a962da28f51","resolution":{"observed_at":"2026-08-05T16:00:39.439485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-08-04T16:31:32.458167Z","title":"Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution.arXiv preprint arXiv:2312.08617, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.13557","last_updated":"2026-05-30T18:21:39Z","snapshot_observed_at":"2026-08-04T16:31:31.943730Z","submitted_at":"2025-09-16T21:52:04Z","title":"MACO: A Multi-Agent LLM Framework for Automated CGRA Hardware/Software Co-Design","version":7},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T16:31:32.458167Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2509.13557"},"observation_digest":"sha256:a26580418dfb0d07ca32389a2191855c9b4426a8b033b0cdf71ea72c3abcafbc","observation_id":"96b644a8-e289-44c1-8858-c40690391dc6","resolution":{"observed_at":"2026-08-04T16:31:32.458167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2604.19856","last_updated":"2026-04-21T17:20:24Z","snapshot_observed_at":"2026-08-05T13:44:29.091535Z","submitted_at":"2026-04-21T17:20:24Z","title":"ChipCraftBrain: Validation-First RTL Generation via Multi-Agent Orchestration","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T01:24:08.563327Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2604.19856"},"observation_digest":"sha256:4761cd263c1567f65adf0dc0e77adb507d3f627e8345887485ae3d5771f9ae7e","observation_id":"0b0a7f71-b9d6-48b5-a3cc-0707e679fa7f","resolution":{"observed_at":"2026-05-11T13:36:08.347789Z","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":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2604.24218","last_updated":"2026-04-27T09:22:02Z","snapshot_observed_at":"2026-07-06T23:10:20.676482Z","submitted_at":"2026-04-27T09:22:02Z","title":"RefEvo: Agentic Design with Co-Evolutionary Verification for Agile Reference Model Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T03:16:00.089055Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2604.24218"},"observation_digest":"sha256:7149b37abee5ab7af997ff95099015c134e07fc7515eb74ba5555fe986013d16","observation_id":"c65e14eb-20fb-4c0f-be4f-0237e24b7389","resolution":{"observed_at":"2026-05-11T22:11:14.615391Z","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":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2605.26498","last_updated":"2026-05-26T03:21:32Z","snapshot_observed_at":"2026-07-06T23:36:20.072253Z","submitted_at":"2026-05-26T03:21:32Z","title":"Verilog-Evolve: Feedback-Driven and Skill-Evolving Verilog Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-29T18:49:52.243940Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2605.26498"},"observation_digest":"sha256:f06e51c8345f2c5b7ce5cd075477440e2c1213956fa43362d3fd9f10ac5f5cd8","observation_id":"d9df277e-bc8c-4616-a08f-81057eef75f1","resolution":{"observed_at":"2026-06-29T18:53:51.265943Z","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":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2606.05253","last_updated":"2026-06-03T14:51:33Z","snapshot_observed_at":"2026-08-01T00:36:11.076649Z","submitted_at":"2026-06-03T14:51:33Z","title":"Alpha-RTL: Test-Time Training for RTL Hardware Optimization","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-06-28T07:11:52.187869Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2606.05253"},"observation_digest":"sha256:361a6ca848f109b61f703bd64f422f2351daafb4fe17b5f6c85ae747e75a1415","observation_id":"848f8f92-28ff-4b6f-9ebc-09323e5031a6","resolution":{"observed_at":"2026-07-02T07:06:44.132730Z","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":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2606.06530","last_updated":"2026-06-19T08:28:31Z","snapshot_observed_at":"2026-07-30T05:17:42.434726Z","submitted_at":"2026-06-03T12:54:32Z","title":"RTLScout: Joint Agentic Code and Synthesis Optimization for Efficient Digital Circuits","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-28T03:58:14.042598Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2606.06530"},"observation_digest":"sha256:235fda6967da334f1ed3bc9b90aa92c17006ac4798b34c444038ab167a1c10b5","observation_id":"5b882b5e-8538-47dd-aa4a-26ae5034d4a2","resolution":{"observed_at":"2026-07-02T11:26:54.355587Z","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":"2312.08617","last_updated":"2025-08-06T13:02:31Z","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution","version":5},"cited_work":{"arxiv_id":"2312.08617","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.08617","snapshot_observed_at":"2026-07-02T11:26:54.353732Z","title":"Rtlcoder: Fully open- source and efficient llm-assisted rtl code generation technique","venue":null,"work_id":"0b595356-7823-4712-a6d8-c6f61a8963d0","year":2023},"citing_paper":{"arxiv_id":"2606.28279","last_updated":"2026-06-26T17:21:06Z","snapshot_observed_at":"2026-08-06T17:12:53.583746Z","submitted_at":"2026-06-26T17:21:06Z","title":"Agentic Hardware Design as Repository-Level Code Evolution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T01:49:07.838897Z"},"links":{"cited_paper":"/paper/2312.08617","citing_paper":"/paper/2606.28279"},"observation_digest":"sha256:95e3b76f840c91121ba094ba1fb9c1e5eba34091dea88a4a978ca02f479ed1d4","observation_id":"439ecdb6-d94c-4c47-ac8e-1f8e756ccc81","resolution":{"observed_at":"2026-07-01T18:45:58.292383Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2312.08617/citation-record","integrity":"/paper/2312.08617/integrity","json":"/paper/2312.08617/citation-record.json","paper":"/paper/2312.08617"},"outbound":[],"paper":{"arxiv_id":"2312.08617","last_updated":"2025-08-06T13:02:31Z","latest_version":5,"primary_category":"cs.PL","snapshot_observed_at":"2026-07-06T17:01:26.660741Z","submitted_at":"2023-12-14T02:42:15Z","title":"RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution"},"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 11 inbound Pith citation observations for arXiv:2312.08617."}