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Paper Citation Record · LEDGER

Insights from Rights and Wrongs: A Large Language Model for Solving Assertion Failures in RTL Design

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.04057.

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

pith.paper-citation-record.v1
2503.04057 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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T17:58:45.319714Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T18:01:54.448333Z

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 33b37b81-9c71-495c-8a62-1f0aaa3fae61 · inbound

From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification cites this paper.

From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification Insights from Rights and Wrongs: A Large Language Model for Solving Assertion Failures in RTL Design

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:01:54.450192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-22T17:58:45.319714Z digest=sha256:a0e9a258412e91c1255ad88e2ec2601aec8927b17ad8d2727df3b16915b633e3

Observation 17750a43-e15f-49fe-8069-0472dbb7bdef · inbound

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench cites this paper.

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench Insights from Rights and Wrongs: A Large Language Model for Solving Assertion Failures in RTL Design

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T17:52:42.987015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-19T17:49:01.198956Z digest=sha256:b201926848f0c40265b669ba0d5ef4d1fb7983d65e41e84df7f5f9927e626298