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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.337750Z digest=sha256:d9fb54b36e08691bd55be6f3ceade2b7860a52aa4f44dfd7e31a5c937f9a87f1

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.392268Z digest=sha256:cd89b5000ace61100a65bf47361f204bfa0a3a5167a7ef7d839d02b4aabc40c9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.500110Z digest=sha256:6f303121754073ca6bb9a892bb86db1f3153a55a4a00546bd7eedb42627c9b5e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.577773Z digest=sha256:69f414eeff44863851ff74d50e0021401190cc524dc4e0c2199f4b38149d07b4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.653786Z digest=sha256:c5dc7240511159044ae4b5f3822b9a27fad09be1ce2adb6f523ee1e748ad584d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.735875Z digest=sha256:5e27471e9dcb2d5577f958b4e403b8d9111216d1bf58ac62600a86d45c2f4f72

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.792632Z digest=sha256:b6c171bc3c9eee2b9e7b78d23e85cb8ecbf570708b5e8793e36d61d6fb7b1ceb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.796727Z digest=sha256:8856ab3dee83e9c24e026036cf0d3e3cbc9047e23b855873301770fc6ca65943

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.800594Z digest=sha256:a66bcb2ed5409d6803726da1ee50e9808a5e21694e0232bd0b5c85bf9873b169

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.804515Z digest=sha256:495d931634986db216c4df94986da7d9abdf3b992600ca961c1a0bec678db8a9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.808457Z digest=sha256:b5cf8e230162626df00e2be609abefb160985e0e9f4460bec43731e6160f2965

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=sha256:5f8c86387503b2dddecad2a44029f720ed9b9f2eef6400d0ac5219705a2135fa

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.815686Z digest=sha256:557c26a4c12a4df04af9c844d77384183b6578bea8b3ec30dbf9f3af13603c4c

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=sha256:97221d731af245bb94c8c59c9509552510b313aecc412117660e117e8695cc45

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.822735Z digest=sha256:7929496c119d383c36027d64bea31e0d6116580267a72fc7a157392457a945db

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.826682Z digest=sha256:f990544865a3dff4c580bce800733f6e33b6789fb3f76274ab8d476c322e56db

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.830166Z digest=sha256:3a31bdc670a3279ecf590c4a84f3a47f3254ba3b5981269b8102bc5aeb68e9ea

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=sha256:5361819e5b637a0cc27c16bad6bdd80d7f533749fda8371cbaf9a6da08cde0ea

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.837210Z digest=sha256:9a263be7c1f40d7cc4e660e2fa6db40cc31c23aac23df7a93fa667305dc39928

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.840608Z digest=sha256:a7e2cb22b79d94f322456baaf6dc5f9f3d1c4835f570d9a7121c78bbda44b80d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.844298Z digest=sha256:a73b63cf0d66c5062fc52c6533baec5ad65a9a49fe6839e393069342f97d8e16

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:e0ad23afc33fe5a51f05451c7534894c1121cd676f3fab7946975a63d8c4bbd5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.851714Z digest=sha256:9cd472117bef78302188a0de7a5b0793319194a270bdd7efe7645da6cd3c4126

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.855215Z digest=sha256:3000f7949edce9a5781063531c3beb733a9d196cfa2f580f200ef159d3ee80fb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.858609Z digest=sha256:1a478259434ee0ee5e74db4521da2886778e44d2a36bdfdad8abfb694c94faba

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.861933Z digest=sha256:5651a177d5a846a1532a16150a7ed4e0532cfb412aa6f54b4bfe004461995066

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.865386Z digest=sha256:62c4a0f3047b7cf0d94c1429e32bf2f22e2a651db1706c8538f07efb39bd156c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.868691Z digest=sha256:861d2680e7fb79a50c7ecc607fbaf9bafe757e45b8442034c724ede9f9d23014

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.872347Z digest=sha256:bde77052d10cc4529d6078c767bc03aa2848ea3736384ab0e2bc4de5dee7d711

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.875722Z digest=sha256:e44cc6a89358c323605639a65c91edafa99f76d24a4ace1ad7043d043cc05ffd

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=sha256:15ccadb861d207ec6a471f8cdfd45ec9a0bfdc3b5e4852740adb0bc946970eea

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.882881Z digest=sha256:d93d3166e82328a809b7280191e176d483418c6990a134caa4d3df6fd3b4b73a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.886575Z digest=sha256:ba84275023d6b4a55498d6fd62ddc51e8de64c5d64ec9b7c92d1beea1363e933

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.890126Z digest=sha256:043a9b9bda2f94eb67681f7a88098b053df60b3b83d919300579d219da2af91d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.893537Z digest=sha256:52cd5180c628728868603375de513b91307a4aaaa7a64d5a67d500d6b3c8b934

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:b80df5cce324a1012b3a5c909abf53aeb119311863f2b778fe7198f9121a17aa

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.900897Z digest=sha256:d8852f071c4c3f0bc09609ce04ceae6b241a30788c65febcac4e9788f3b14ff0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.904392Z digest=sha256:74441f69e071e1b01ec0ec55a9aa22538f73cc53ecdac0bf6165b4d39de13a18

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:ad37ebb9d3be74173e2a24e5298b55aebcb43f9bdc92ff2b480540621e85a3f9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.912291Z digest=sha256:34285e4e701a1915bf529ea33206641e4256ccdb33570d57c1115f7dcff4e277

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.915922Z digest=sha256:acfe9f392363fc4615507d599c7ccbbd7eefeb72903fc68ca1a536f0705d95c7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.919497Z digest=sha256:a479af586f36a92328372c11c2a01e523108dc20f1d02922b5bf25e53ef1a84d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.922979Z digest=sha256:abef2b0bbaaae7401973dca9c5b9997849c9d06bb90177d03960bdce7da9268d

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=sha256:46a1a0c63aa4d8bcfeda49c44f861eabf23704f647bb6bbac60376cbea01fba7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.930036Z digest=sha256:6e442adc0f6b14deb242ce8b1196c3b217acb51fbd4401dd2d535d85c3939088

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.933515Z digest=sha256:a6964cf735e2b178f935522902c9d85a453044bcd1b81ee57a2a21c3f96d4a4f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.936897Z digest=sha256:21f9063e1695881219188b193e59b0f45aa59305b8539e78fed2479282d62d29

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:eb8c3b56bfc5bbe827bb63c760539fdc65c1983dab62ec5cc0f6a54f260acfcd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.944157Z digest=sha256:e21c5240e126f753c36e7e14759ecdd6aa65c2748c808e81f1e59401d2edd6fb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T05:50:29.947770Z digest=sha256:45fd4b774c98ac5fdf03ab6320fe358b5fdb9427729e89be7d160b384fd7998e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T06:51:24.566343Z digest=sha256:7c918e5307fd352e9309c26fc22f90118eece9f08ed2eed4876c93926945e43b