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Paper Citation Record · LEDGER

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design

As of 15 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2509.04905.

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

pith.paper-citation-record.v1
2509.04905 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:50:29.947770Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T06:51:24.566343Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T06:54:01.144171Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact2
  • verified fuzzy39
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fd77270-fab5-48aa-8dbc-006449bf2dff · outbound

This paper cites Global semiconductor sales in- crease 19.1% in 2024; double-digit growth projected in 2025,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Global semiconductor sales in- crease 19.1% in 2024; double-digit growth projected in 2025,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.753804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.337750Z digest=sha256:08104bea46b67c117d9173c24fd2f90dcaab712645d1d142579765e5c88e2974

Observation 26dcffd5-7f75-4906-95d7-52982660182d · outbound

This paper cites The semiconductor decade: A trillion-dollar industry,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design The semiconductor decade: A trillion-dollar industry,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.742599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.392268Z digest=sha256:be8833a0b1824351d059d086319db2da09f15f4e4b14a3bb5bd30a5ea0ee3cb1

Observation 928c24d9-890f-4d51-ba7e-8d40c30c8ae0 · outbound

This paper cites Electronic design automation (eda) global market report 2025,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Electronic design automation (eda) global market report 2025,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.731121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.500110Z digest=sha256:de0497094ee3d149c4234a6453de0ba9079ed3a8c99b57771e09766e2c2967f0

Observation a6553b11-c539-430c-bf52-a438fd66629c · outbound

This paper cites Machine learning for electronic design automation: A survey,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Machine learning for electronic design automation: A survey,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.719747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.577773Z digest=sha256:1c696fc21dc86b4c8973cb00b5a581fbdabc6dd046c2363157932ab1f69563c3

Observation 3fc23f03-6e02-4ca6-8801-c0f75c067e7e · outbound

This paper cites A survey of research in large language models for electronic design automation,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design A survey of research in large language models for electronic design automation,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.708484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.653786Z digest=sha256:2a607735b84027e7cd86e943dac5748559860c0c286e665021c7725182633b61

Observation da7fea96-c237-48ef-82bc-2d9ac082f58e · outbound

This paper cites Chatcpu: An agile cpu design and verification platform with llm,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Chatcpu: An agile cpu design and verification platform with llm,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.696305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.735875Z digest=sha256:60b2c8c7d930ff209669d62efbc62aaee45c7e56fe5dfae172387d42fc3d3399

Observation cc294d16-cd06-47f2-a00e-7a048ef9531c · outbound

This paper cites Llm-based processor verification: A case study for neuromorphic processor,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Llm-based processor verification: A case study for neuromorphic processor,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.684573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.792632Z digest=sha256:cdeaa69b1ca00e83da3df171a931a7925fb65ab7d7294ce0ae9f2722184d67d7

Observation d52c5a49-458b-4b17-b10e-5fbfe1170a4d · outbound

This paper cites Llm-guided formal verification coupled with mutation testing,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Llm-guided formal verification coupled with mutation testing,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.673002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.796727Z digest=sha256:e6c1f5a383436c717bf10b98f90b49531c2b3056c0f05bcb7557f5c7186e5713

Observation 72ce8098-054a-4324-974e-d324f7cead4e · outbound

This paper cites Rtl- coder: Fully open-source and efficient llm-assisted rtl code generation technique,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Rtl- coder: Fully open-source and efficient llm-assisted rtl code generation technique,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.661612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.800594Z digest=sha256:e1dd001944e167e2ca9abe7018d75ac891f298db83c0746f50fb031f9984a91e

Observation 6b93d49b-adaf-4a91-81ed-922edaef86d0 · outbound

This paper cites Verilogcoder: Autonomous Verilog coding agents with graph-based planning and abstract syntax tree (ast)- based waveform tracing tool,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Verilogcoder: Autonomous Verilog coding agents with graph-based planning and abstract syntax tree (ast)- based waveform tracing tool,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.650302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.804515Z digest=sha256:0a52111693bf55383529b229a3fe51ea2b108bbdff11c2a89c941c671fbe1232

Observation c09b8900-6a99-488e-9aba-27fc46f472ab · outbound

This paper cites Large circuit models: opportunities and challenges,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Large circuit models: opportunities and challenges,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.638556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.808457Z digest=sha256:6e45ef27b8ccfe5ec4c967c08185d8d6b7e06489eafb1bd7c75187e940821b9d

Observation f5166c0a-5020-4d7a-9c3d-14c73dde9273 · outbound

This paper cites Chipgpt: How far are we from natural language hardware design,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Chipgpt: How far are we from natural language hardware design,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.811928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.811928Z digest=sha256:d50edfda40c1cd776977365685a700fe2d40397e92ddb5df34b3cf069c8552c9

Observation a0f3621e-d127-43e4-adeb-fa0e1edcec1a · outbound

This paper cites Revisiting verilogeval: A year of improvements in large-language models for hardware code generation,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Revisiting verilogeval: A year of improvements in large-language models for hardware code generation,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.626507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.815686Z digest=sha256:07f6999baa0072a22e9ad8fd383215ba96d5956d1623db78bfe30ce679de94a9

Observation 4fefa38d-41cd-4acc-9549-bf39075cadd6 · outbound

This paper cites Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.819033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.819033Z digest=sha256:39e770c6716c72a5c497073f091988983b830338703863474409eb3783ca3d4a

Observation 94643c6e-396b-4892-93b0-51838d862ae3 · outbound

This paper cites Betterv: Controlled verilog generation with discriminative guidance,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Betterv: Controlled verilog generation with discriminative guidance,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.614473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.822735Z digest=sha256:28fed20ed7844503ef8a1170a4f1dc6f36a3ed2f20053ecd6b07c569e5716b45

Observation df8e1062-732a-497f-8858-0b5feff5b34a · outbound

This paper cites Deeprtl: Bridging verilog understanding and generation with a unified representation model,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deeprtl: Bridging verilog understanding and generation with a unified representation model,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.602901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.826682Z digest=sha256:bd9132f5d79aae30aacaf02b082c3e9b3cfb660c123d47f02d9509ae63bd6350

Observation 878372e9-9a00-4549-8975-1b85d1f2e024 · outbound

This paper cites Deeprtl2: A versatile model for rtl-related tasks,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deeprtl2: A versatile model for rtl-related tasks,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.591501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.830166Z digest=sha256:b175dba4163d7fffc2c17a2c5a66c129aaf6736f4dd99515ee31889fd1a4eba8

Observation 32838db4-89fc-44d5-a738-2bdf99f2f5bb · outbound

This paper cites SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.833591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.833591Z digest=sha256:7fbec78779762d756a798ad5da41374e004c73630a67d69c091dfc0c3204cc96

Observation 843aeaa3-db56-4441-8ade-b17d343631a9 · outbound

This paper cites Assertllm: Generating hardware verification assertions from design specifications via multi-llms,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Assertllm: Generating hardware verification assertions from design specifications via multi-llms,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.579569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.837210Z digest=sha256:48be8fe2f6211c3c0d671c3e39a8c3da77bdb94db906fb008f7d0e96550fd25a

Observation 81fcaf07-9373-470d-839d-82daccfe3440 · outbound

This paper cites Assertionbench: A benchmark to evaluate large-language models for assertion generation,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Assertionbench: A benchmark to evaluate large-language models for assertion generation,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.567397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.840608Z digest=sha256:84177161c29c3397eee510ae3286530ad9978fa658cd69b260235bc79f94b8eb

Observation e553c74f-68a3-41ef-8660-8b94468e158c · outbound

This paper cites Rtlfixer: Automatically fixing rtl syntax errors with large language model,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Rtlfixer: Automatically fixing rtl syntax errors with large language model,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.554297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.844298Z digest=sha256:8d34861d5a29a0e01842f78a3c53acc51791574f7e1e0c669306e98d8bd180da

Observation c732ae9d-b738-4392-908c-b06fd4192373 · outbound

This paper cites ChipNeMo: Domain-Adapted LLMs for Chip Design.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design ChipNeMo: Domain-Adapted LLMs for Chip Design

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.847849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.847849Z digest=sha256:4b2b51ef860e998d44f3c7d56b5a44d7fe6ddae98af9ccb9ebb5e357934d26ce

Observation c551e8e4-73a1-431d-8f41-79664b5b503c · outbound

This paper cites Customized retrieval augmented generation and benchmarking for eda tool documentation qa,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Customized retrieval augmented generation and benchmarking for eda tool documentation qa,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.541541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.851714Z digest=sha256:a019665ed819ec1795a2f4aaac2b2c575ce063b433eb721e699dfbb4c469c697

Observation 1e3fb026-3f97-4767-b0ce-9c236a3d5c93 · outbound

This paper cites Drc-coder: Automated drc checker code generation using llm autonomous agent,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Drc-coder: Automated drc checker code generation using llm autonomous agent,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.528394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.855215Z digest=sha256:d9d180e75798fd3ec18d96af82766f2dbd028d6545c031064e84b82a1a116e3c

Observation aee644d1-4d37-4bc2-a351-bd2672758ff7 · outbound

This paper cites Rtlrewriter: Methodologies for large models aided rtl code optimization,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Rtlrewriter: Methodologies for large models aided rtl code optimization,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.515132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.858609Z digest=sha256:7963d500fa61a5dd6a47d8640120b3a3bf5df80a3b8ad75b849a53be11dcdace

Observation 5a50e2d6-6a2d-4b62-86f1-1e62bb874444 · outbound

This paper cites Deepgate: Learning neural representations of logic gates,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deepgate: Learning neural representations of logic gates,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.503066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.861933Z digest=sha256:4d3c8473b4b0f3baeb9242f5d24ac9b9fb645af3a6062fc016dc548fbb92682c

Observation 09efadab-49e2-4f08-b6fe-5aeaf7de115d · outbound

This paper cites Maskplace: Fast chip placement via reinforced visual representation learning,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Maskplace: Fast chip placement via reinforced visual representation learning,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.489739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.865386Z digest=sha256:94e8cd398e1d5667cc228887b45f59e2461a786ca05cfb6ffa47e65a76dc59bb

Observation 34e5885f-17bc-49d8-97a0-495a43b2fa5a · outbound

This paper cites Deepgate3: Towards scalable circuit representation learning,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deepgate3: Towards scalable circuit representation learning,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.476144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.868691Z digest=sha256:77cd2d1791d23a108fb03799f51c64adc9d539ab133e0d87b7c885976e1e6d66

Observation 8631836d-890a-4349-9a1a-9040b5e37517 · outbound

This paper cites Deepcell: Self-supervised multiview fusion for circuit representation learning,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deepcell: Self-supervised multiview fusion for circuit representation learning,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.463790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.872347Z digest=sha256:3b365d973df109025b44eef762f3b71c3391191eb334fb7e0a88e60a21693063

Observation f246af36-f983-47f3-9aee-7c32eafa3b76 · outbound

This paper cites Circuitfusion: Multimodal circuit representation learning for agile chip design,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Circuitfusion: Multimodal circuit representation learning for agile chip design,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.451303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.875722Z digest=sha256:ecef8ef67bef351ac417bf994567f6cd71fe08e1a6032d8352c34c0ac14877c0

Observation 940ad1a5-aa06-439e-861b-192380c0f889 · outbound

This paper cites AutoChip: Automating HDL Generation Using LLM Feedback.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design AutoChip: Automating HDL Generation Using LLM Feedback

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.879093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.879093Z digest=sha256:25c8595ce6950d9842d15f4484c70737b7a6e7005c84273f408295ee720e67fe

Observation 4cb5c1a9-d943-4722-be97-8b0f37983dbf · outbound

This paper cites Autobench: Automatic testbench generation and evaluation using LLMs for HDL design,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Autobench: Automatic testbench generation and evaluation using LLMs for HDL design,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.439109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.882881Z digest=sha256:7a7355680d9a6b8d76316977c6ece27983fb7a7e1f4067b1ce029cacfee6d2c9

Observation 2c778a2c-e9b4-43d5-9118-1e1957dbc488 · outbound

This paper cites Uvllm: An automated universal rtl verification framework using llms,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Uvllm: An automated universal rtl verification framework using llms,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.427306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.886575Z digest=sha256:11e8444cde5f86e38270de5f81c29355c03db454862a7e0577fb309514d252c4

Observation 3098f8b9-262f-4e46-b733-7f556890a0b9 · outbound

This paper cites Llms for hardware verification: Frameworks, techniques, and future directions,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Llms for hardware verification: Frameworks, techniques, and future directions,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.415528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.890126Z digest=sha256:b6fae04987935822a47c9b433b936f220fabfe1a385c938c4a138fe27bca2d0c

Observation 3b2f21e8-979b-4df9-ac80-72b19c842614 · outbound

This paper cites Prompt. verify. repeat. llms in the hardware verification cycle,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Prompt. verify. repeat. llms in the hardware verification cycle,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.403344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.893537Z digest=sha256:335a9778e35febf6edcae516702f93f8a1a8b4ac8c8ff6223557cfffa073011c

Observation 68ada99a-d079-4f5f-8b4a-80a850cec4e5 · outbound

This paper cites ChatModel: Automating Reference Model Design and Verification with LLMs.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design ChatModel: Automating Reference Model Design and Verification with LLMs

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.896944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.896944Z digest=sha256:ffd76c662380eb1251d58781d03bcaebc60d4706f1746bca1cc9730926fc406b

Observation 3c381054-0bc8-4905-a46b-5873b0afab9a · outbound

This paper cites Meic: Re-thinking rtl debug automation using llms,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Meic: Re-thinking rtl debug automation using llms,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.391522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.900897Z digest=sha256:bea68b09ca5dc168e64da55857d06a337228365d1e8ba58982042e29c2c4119f

Observation be6ce78f-e184-4b37-b94d-94f4063a2c1d · outbound

This paper cites VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:50:30.148024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.904392Z digest=sha256:fe6b2d19ba021d490df3382f2b4c384930bc2062dba24a61a3239947a733dd76

Observation fcf90e96-9f77-4510-b137-53b4ac61dc1c · outbound

This paper cites Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.908555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.908555Z digest=sha256:e4d159c4489292fb4edd1a6ab31251f40a3865c6dd4faa80ac9b02a62e07a82a

Observation 7533358a-8a4e-415a-b4c7-c214ea7cf193 · outbound

This paper cites Improving llm-powered eda assistants with raft,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Improving llm-powered eda assistants with raft,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.379366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.912291Z digest=sha256:978e12372e9363d0d0d48b3e980ad3425f510e003088164e19e5ff1e15fc21d6

Observation df1baf80-5600-41ea-871f-9338f38236e2 · outbound

This paper cites Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:50:30.015038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.915922Z digest=sha256:0075c4f127d831fb46f8189c8e385f3f287f7669164cf7e4c89cee6e9d150c50

Observation 776b5908-72d9-40b0-a4ba-957165aa8ac0 · outbound

This paper cites Accurate predictions on small data with a tabular foundation model,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Accurate predictions on small data with a tabular foundation model,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.367616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.919497Z digest=sha256:2c07916e64f136daab826de1806f55a94a9b4e34e9ff30a4765af7138f472d2b

Observation 5fb13fea-8ee8-40a3-926d-bfbb9c81b274 · outbound

This paper cites Transformers can do arithmetic with the right em- beddings,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Transformers can do arithmetic with the right em- beddings,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.355605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.922979Z digest=sha256:a59d10b3adca8874d28c1a9a2eb81f85423e95166a74513a35c6cf4016975795

Observation bbe6fbef-3632-4184-aec0-93c95c66c9c0 · outbound

This paper cites The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.926202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.926202Z digest=sha256:342b55cb8369e6419bb9186c46796e67a6996df963802595d6bfe5d6f0c3b41e

Observation 9156f28c-27aa-43a7-a539-2336b1ddfd99 · outbound

This paper cites Measuring the impact of early-2025 AI on experienced open-source developer productivity,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Measuring the impact of early-2025 AI on experienced open-source developer productivity,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.342349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.930036Z digest=sha256:c8608e1d5ce1ed54ac3922f60cbe1e46ec84fd8424d1bdfa6cd7902b0398eac9

Observation 03180307-f73c-4d60-9ff9-e426a1c915cf · outbound

This paper cites Correctbench: Automatic testbench generation with functional self- correction using LLMs for HDL design,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Correctbench: Automatic testbench generation with functional self- correction using LLMs for HDL design,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.330234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.933515Z digest=sha256:cf7b2784a2c3dddf13c2300121008ba5e7360811c7302b302a163fc9896a5a48

Observation 9cbde998-b836-43d1-b146-ee5aa4cffb23 · outbound

This paper cites Genben: A generative benchmark for LLM-aided design,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Genben: A generative benchmark for LLM-aided design,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.317623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.936897Z digest=sha256:d8715294262df3aadc0e830b7fc4824702e5f040909c169831f2f58c8833af48

Observation 906a3cae-8dbb-43c1-9f09-55e02d796b6d · outbound

This paper cites FIXME: Towards End-to-End Benchmarking of LLM-Aided Design Verification.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design FIXME: Towards End-to-End Benchmarking of LLM-Aided Design Verification

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T05:50:29.940447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:50:29.940447Z digest=sha256:2bdb757aa9e5ae12172b3ee897592dd66e0c6a957fb677c128915289aa92cf61

Observation 935d7aca-44df-4213-82fb-a32c07c45627 · outbound

This paper cites Deepcircuitx: A comprehensive repository-level dataset for rtl code understanding, generation, and ppa analysis,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Deepcircuitx: A comprehensive repository-level dataset for rtl code understanding, generation, and ppa analysis,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.304955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.944157Z digest=sha256:f49b7a55bf6b315a2500c621a86446f466be727d087ef2c77f348afc8af77cf0

Observation 2f59ac46-8e54-4768-bc53-87921a52c46a · outbound

This paper cites Forgeeda: A comprehensive multimodal dataset for advancing eda,.

Revolution or Hype? Seeking the Limits of Large Models in Hardware Design Forgeeda: A comprehensive multimodal dataset for advancing eda,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:50:30.292586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-05T05:50:29.947770Z digest=sha256:13193f96eb018c1151530a28db78754328e755ac36602d4cb7173915fbce0d5e

Pith citing papers

Observation 9fbda0b2-cd40-44c6-9c73-e11200c60634 · inbound

Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development cites this paper.

Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development Revolution or Hype? Seeking the Limits of Large Models in Hardware Design

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:54:01.145807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T06:51:24.566343Z digest=sha256:fd33f3e3821e05de53356667023a8c82421998c80b8e6b9048c533b277db0144