Paper Citation Record · LEDGER

Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2402.03289.

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

pith.paper-citation-record.v1
2402.03289 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:31:00.609981Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:26:54.350822Z

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 369601cc-f9c9-47ce-a1f6-1b54753b72e8 · 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 Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-22T18:01:54.473377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f1a4fe0-a4b3-4ebf-a038-785f8326e3e9 · inbound

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems cites this paper.

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:31:00.609981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4e2fe84-5046-4326-b656-255c34711c6a · inbound

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

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:52:08.340207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation af43cb1d-c51d-4b0e-ac70-3883be5cc64c · inbound

VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs cites this paper.

VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:51:34.497654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d78ba97-106d-4bbf-b7c1-0f6d9c6e01ef · inbound

Dr. RTL: Autonomous Agentic RTL Optimization through Tool-Grounded Self-Improvement cites this paper.

Dr. RTL: Autonomous Agentic RTL Optimization through Tool-Grounded Self-Improvement Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T10:49:56.144826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3820a852-666b-4c3a-aa80-70d442737c8d · inbound

ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation cites this paper.

ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:55:42.806344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 98e0710d-a095-40b1-820b-0b862bdd37f5 · inbound

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges cites this paper.

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:51:26.516610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 06ada91e-3772-4922-a22d-541d50dbca12 · inbound

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges cites this paper.

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:12:58.732233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b62fb439-bbb5-4ce7-88ee-3871a9b4a95d · inbound

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges cites this paper.

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:59:55.413370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6aad461c-3e86-4873-b72f-9443c4c50da9 · inbound

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges cites this paper.

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.807555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 45e8283a-f7e7-4ba8-8589-a84a87723704 · inbound

RTLScout: Joint Agentic Code and Synthesis Optimization for Efficient Digital Circuits cites this paper.

RTLScout: Joint Agentic Code and Synthesis Optimization for Efficient Digital Circuits Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:54.352561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 41c6e913-4222-4abc-a9c7-06c2a20c5e47 · inbound

Hardware Design and Security in the Era of Chiplets and LLMs cites this paper.

Hardware Design and Security in the Era of Chiplets and LLMs Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T10:13:17.736131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.