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Paper Citation Record · LEDGER

RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.11414.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.11414 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:57.333888Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T14:42:37.300033Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 07a7521a-01d5-4ff9-8b2f-b3d3512c4ad5 · inbound

ReChisel: Effective Automatic Chisel Code Generation by LLM with Reflection cites this paper.

ReChisel: Effective Automatic Chisel Code Generation by LLM with Reflection RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:11:57.333888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:11:57.333888Z digest=sha256:11186e582abfa1d5dca1bc203b0285e3a7d31866c82e0ad7eaa8c57e77f2ec1c

Observation 8db082dd-76ef-4d61-a987-ff36c8bf4fee · inbound

VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code cites this paper.

VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:46.257689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:43:46.257689Z digest=sha256:c7b5914aeccd605c30c8f45e6d844963d5851d48123cb8120cb389ad14bd9b1d

Observation 01bb3927-ee07-4999-b435-5411213d6122 · inbound

DecoRTL: A Run-time Decoding Framework for RTL Code Generation with LLMs cites this paper.

DecoRTL: A Run-time Decoding Framework for RTL Code Generation with LLMs RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T20:40:17.127598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:40:17.127598Z digest=sha256:2e66851ad1a0ec27d32c383215baaf81d5900817c0d6be39eea6bcc85c83b1cd

Observation 76c0da57-48eb-4fa2-a721-8012c0959822 · inbound

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning cites this paper.

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-19T06:52:08.261925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T06:48:29.015759Z digest=sha256:63815de25b1ffbc8c5787a88163983fbeac0475f352eff4e7005d9aac1c8d9be

Observation ad6362d0-0e6e-438e-baef-b3c23f524025 · inbound

RealBench: Benchmarking Verilog Generation Models with Real-World IP Designs cites this paper.

RealBench: Benchmarking Verilog Generation Models with Real-World IP Designs RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:53.025192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:53.025192Z digest=sha256:bd90c47e7279c05318e1987493a745b7c7ef0f42cb0c6597828c35344c94a4af

Observation 9886c5b5-a343-445f-ae03-58635c91d9c5 · inbound

RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision cites this paper.

RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision RTLRewriter: Methodologies for Large Models aided RTL Code Optimization

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-19T14:42:37.303419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T14:42:16.802186Z digest=sha256:24d8a3dcaf7e59ce0c99d56490ad7dc7a2a500db71e28d83a516b114dce48aba