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Paper Citation Record · LEDGER

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

As of 19 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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.337750Z digest=sha256:7f96b0f7838a4cfbe915face8658c3fe7b0d55b105b540b1e724fbe5f3175974

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.392268Z digest=sha256:00b488b73d6865af1e59c95dec1d27cfe424313cdebf497ecc86bab4fcd66b99

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.500110Z digest=sha256:9c70f251855b7d860735c6e70d8ad3bd1ba1b03c89744d94b7b9783c62222236

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.577773Z digest=sha256:89aade3f4ac96d10c31e160a6f8dfc5b1ffaafd33abdb0fc1709fcd41551fb3b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.653786Z digest=sha256:249971c74c04e0eaa0123bf6dd92226622dd615af21bfd63ebfeea8c59dc30fb

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.735875Z digest=sha256:d74e948c85f502a6bdefe29390c32618c2ce997950b622cf2b5d7b287e1e99f8

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.792632Z digest=sha256:c27247332b9845e5ca287b287c8860ff9b923a6f997a884beb3bc07630d524d4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.796727Z digest=sha256:e6884e8cc7dc0d9bdac886b5214685c556f7084574cdf73bf126a742994e684d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.800594Z digest=sha256:2082f78c885637f82cddf1507126cfff4ea61bf9158a015a0dc03c9c7b1e5320

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.804515Z digest=sha256:a206cb9375fbcab9a57881ad7641a0bc96d6b07c5e3f1e82f6e6bc42727d1a93

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.808457Z digest=sha256:3e15149aeff1e11c808f00fff0c262c945a88ea81e731c1f9561635abe2eb283

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:ed62ffee20aa3941ef83496183cf01afe266607c7bb2b9e683d5c731e533ac08

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.815686Z digest=sha256:e994323d155acd21e824109836518c0e43e07530a4be3e8481e86f188f4b091f

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:bf1f85701e6d3cbe5ddbfc25b4252f5e262d62afa25dd1e66ad770b92d392241

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.822735Z digest=sha256:c705eb8eb676bcf09e033c0d69eaf4ad5696dc608e26679afb2cf0e88a06e96d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.826682Z digest=sha256:c1af6ce81b78bd4656f1fcbb2030802929e93a58ac77dbee8610ae46508da5a8

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.830166Z digest=sha256:5ab469b1bd603303d1d4a389ff0cf7fbf37c2ea7f24fe8d3edf64749aadee7b7

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=sha256:04ab68e8d1d44ebc4c1e8f2fa8bc75abcb5282f5fde531e5d4df8bd95c9a484b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.837210Z digest=sha256:0ee54c6e0fc04994b26abe08289dd65097d499f813e49cd67db9bafe7724f0bd

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.840608Z digest=sha256:39e3318ca028ad965ead51f71cf8fb9ba09cd13ae7b8622e804d8f2dae442e2f

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.844298Z digest=sha256:12ed391eaeca539968802bc123498099e524cf56d5c97bebef0c0b640401df3f

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=sha256:60717217cf59abfcdb32a307ee8254300f5ccc3201d232cd7af33b18f2526c65

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.851714Z digest=sha256:84d189397a36656422c5a0ed72e5b86816859e09e2bc9d0bd13b25076bbfed9d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.855215Z digest=sha256:6c5b0490548d5717abcab2a01ce65b41b18ed5af5f936701deb82412e08e2c91

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.858609Z digest=sha256:9189d9e30d8b01efe1fd5d9e51041aa04cf9a31e8f04b7b1971855e48f7bf4ba

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.861933Z digest=sha256:9bf3c5cb0afb2453f7f46534151cc3c8a52b84212f391ed7253eb8e29be4d60a

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.865386Z digest=sha256:b194a90a21e8bd4484c065758887a74bf4591a8cb98fab5491189d4ea787872b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.868691Z digest=sha256:351482e691e08b3ced6b7d6d30fcd80d3dbc769b29ffa237535da9f22a14cb57

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.872347Z digest=sha256:5c28004f8527d5e867dc0fb065e7734cf82e6eb57a16be020af8bc7a2338dcf0

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.875722Z digest=sha256:26f4cb54492b80c0bd97a7b46c63a9d13921ef9d3121d606e2c8a8c5601e4192

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:e24463d83d8e3d000688f4742bb630799de5cf3280a8999185f2f78b70e73fbb

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.882881Z digest=sha256:a1f1e6e94fe562bf31e34ebf3dd25e505d3307621ea5450277856d62dac226fd

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.886575Z digest=sha256:756daf7eac8dd0e5ba4515e7f9c5c37e4a09a429b8b85b8304bcc5d8db3ddf6a

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.890126Z digest=sha256:c236f6a0f61fe007cad686bc24308b18b53d75f1f85a71a095275b4414e23df4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.893537Z digest=sha256:3ca81eed2b13aa09d4fd1b1e323d54a2bd83f7466aa130941c403e2042c4885e

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:beac2ec08076905006f39e5c571418fd973c423dfe6bb934ba51502e84403c40

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.900897Z digest=sha256:d03eb8aef06dee7b11efbbefaa1b2e903b18b6005c9b60592f6c5265d6c1cb5e

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.904392Z digest=sha256:dfc672f3fe3abdb190b91c7b243845fcc7023946353c2f38a95d1f6a32a379a4

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:dd060158d60b0b287fa02735edd6e345c4a7f8c83c9b9e775d5c00e6f9f485ee

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.912291Z digest=sha256:e5b8b7d8a13c0c031615af3fb0d4eca2349c7786f3003a5d7f274684756e075c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.915922Z digest=sha256:ec7b62808156be9d360b1e1d4e103c7e2a36292ddb5c7b026be5001865a326b4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.919497Z digest=sha256:62751f6580537ae7ec587899a4062fcde964f2a7de368070968b62df391a3c15

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.922979Z digest=sha256:542727bd06b0be783b8a8f899200d07f6cc5d8888971411c0e21c1a7cf27bb06

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=sha256:6030fe8214fdaf988003b36f50aedd046cc616d128ebb10602bfbdadc66172ba

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.930036Z digest=sha256:338ea64d75372e89845d7402450c08cd480a7758025d4e4601464ad3fd8e979d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.933515Z digest=sha256:f621c2cd31ae2a5dd52b62ffbef21516f0d34007db4aea413d20ab6013887e70

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.936897Z digest=sha256:d807f05fec6a936cb30f606f640c52523c204d25d81ea6c203708d2d1a55ea6a

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=sha256:4b61b9ad89de95e65e91f691350ee7d6aa3777175a45a8545e28c2c5628e9ff1

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.944157Z digest=sha256:9ad50ada65d188d8dc566604a646ba6b7a9112acfadca89559911908c603cf8d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-05T05:50:29.947770Z digest=sha256:72729f498767cbd2dd3fa4e240f92c1335601f441ce20f22831a7affc9937ff4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-21T06:51:24.566343Z digest=sha256:876360cc6cf8752412e7d10cc6a111d90ca5e8116b30ddfa72c367cf8493e2ad