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Paper Citation Record · LEDGER

Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.08473.

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

pith.paper-citation-record.v1
2407.08473 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:47:16.478725Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:19:55.464670Z

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 70bde7e2-afaf-4939-b64b-2e0c5d52b1d5 · inbound

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

RealBench: Benchmarking Verilog Generation Models with Real-World IP Designs Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:55.561303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T15:19:53.881565Z digest=sha256:279499b5a1580230f20e9cec0e619ecfdbd14d1cc7736966c7f67fff14a14baf

Observation cb354ab6-fc00-429b-8e3c-35e283ce1780 · inbound

TD-Interpreter: Enhancing the Understanding of Timing Diagrams with Visual-Language Learning cites this paper.

TD-Interpreter: Enhancing the Understanding of Timing Diagrams with Visual-Language Learning Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:47:16.478725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:47:16.478725Z digest=sha256:93606306a7efb25e1d3e09182393cd88a5cc4a556524a71506d4fa84c57d7d70