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Paper Citation Record · LEDGER

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 6 inbound Pith citation observations for arXiv:2506.05566.

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

pith.paper-citation-record.v1
2506.05566 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:04.998158Z

measured 59 of 59 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:31:00.525028Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T03:37:35.793348Z

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 200f87cc-c7c2-4b8c-9308-4dee56a96727 · outbound

This paper cites Nemotron-4 340B Technical Report.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Nemotron-4 340B Technical Report

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:18:56.338439Z digest=sha256:2d5802248f8107def7e8bc9030f9ff2856c3c7eaefed357da563d0d2749cfb26

Observation 1bac7b13-8285-49bf-9c06-28a084cd7d80 · outbound

This paper cites Claude (oct 8 version).

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Claude (oct 8 version)

Reference 2

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raw_fallback, observed 2026-08-07T10:19:11.178621Z

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=2026-08-07T10:18:56.514763Z digest=sha256:86302ce0c850466c2a44329ac131eee0e3c5dbdd0c2f9de30e2d0a56ae7c3671

Observation 35bab5f3-5fee-4ed1-a5b1-347f9ee91420 · outbound

This paper cites Program Synthesis with Large Language Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Program Synthesis with Large Language Models

Reference 3

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source=pdf_text observed=2026-08-07T10:18:56.793669Z digest=sha256:5aa93444b00b82265c0d43c37c44b3882ec4386a1b45a3d06d3a3b520573bc2a

Observation e11427ce-62d7-4ca5-a136-0167e4488846 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Evaluating Large Language Models Trained on Code

Reference 4

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source=pdf_text observed=2026-08-07T10:18:56.993157Z digest=sha256:0418a5ba5e88061803268210071021d6ba5919155e1d9e0f229b386209efd1e4

Observation 9c57d182-b096-40a0-8b22-d1832d60ca7b · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 5

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source=pdf_text observed=2026-08-07T10:18:57.148297Z digest=sha256:4835fe48b7154bd4b3867daf54a66fbc81f0d0d94aca8d2ba1748924f5a5e69f

Observation da9fa859-daa5-4edc-8391-0c071acebd9b · outbound

This paper cites Origen: Enhancing rtl code generation with code-to-code augmentation and self-reflection.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Origen: Enhancing rtl code generation with code-to-code augmentation and self-reflection

Reference 6

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raw_fallback, observed 2026-08-07T10:19:10.906887Z

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=2026-08-07T10:18:57.287008Z digest=sha256:624eda1747f4b12f62d53bfb7c7f7bf7756829544082788ca483062ad4d27272

Observation 2e21133f-de9e-4342-a340-1738f3805185 · outbound

This paper cites Competitive Programming with Large Reasoning Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Competitive Programming with Large Reasoning Models

Reference 7

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source=pdf_text observed=2026-08-07T10:18:57.485714Z digest=sha256:97a570e42d37af75661c75e0e49a79197466bd36048c5fa47df923142d80154f

Observation c10134bc-bef6-480f-a17c-ac3eb8cb041a · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Gemini: A Family of Highly Capable Multimodal Models

Reference 8

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source=pdf_text observed=2026-08-07T10:18:57.636945Z digest=sha256:589af81cd7e26a08cbd34ea7f0906cd2a7e22ca71d14374c59dd2c9c292d19fe

Observation 73294458-a928-4dfe-aa4e-f54ec1dc357d · outbound

This paper cites The Llama 3 Herd of Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation The Llama 3 Herd of Models

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:18:57.823442Z digest=sha256:dc3beba91b50c273e3a11c878a89b1ff85bd2d6688b3cf85481edabd332003bd

Observation 51f1b803-696b-4087-94d3-f3b7d800aa4c · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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source=pdf_text observed=2026-08-07T10:18:57.995006Z digest=sha256:7c7d4c8dbcfb19e747093ca0f3ae8edea28848b4e5b0e5c11f278b8b058d826f

Observation 5f9fb1d1-7e92-42b8-afe1-321d42aa8edd · outbound

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

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Verilogcoder: Autonomous verilog coding agents with graph-based planning and abstract syntax tree (ast)-based waveform tracing tool

Reference 11

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:18:58.121201Z digest=sha256:a402cee40e90db3e4ec4ed8c1388322bfb1957271a58cb417704653595ebfcd8

Observation b97d11db-22cf-4e67-afcf-7bddecc56fef · outbound

This paper cites Training Compute-Optimal Large Language Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Training Compute-Optimal Large Language Models

Reference 12

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source=pdf_text observed=2026-08-07T10:18:58.298950Z digest=sha256:389476c6a7aecbf431cdc675ea2a4edb3679465f032a7c366f99b7f1658565dd

Observation 3b6804c9-9e4b-4482-ba9a-ef7a97f30215 · outbound

This paper cites Qwen2.5-Coder Technical Report.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Qwen2.5-Coder Technical Report

Reference 13

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source=pdf_text observed=2026-08-07T10:18:58.442329Z digest=sha256:9c09efc3705b0649b90917595f0b32b2d83289482d965d9b027e0ace67b5b2ca

Observation effe6982-bee5-45e4-87ab-783df2cad06e · outbound

This paper cites GPT-4o System Card.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation GPT-4o System Card

Reference 14

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source=pdf_text observed=2026-08-07T10:18:58.570685Z digest=sha256:f8e9855c8919545cae8baaf3c8fd1c6258bb0db86e2a500371708556e0cc11d8

Observation 929919e4-02d1-4985-bb63-5e21a4b05b34 · outbound

This paper cites Scaling Laws for Neural Language Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Scaling Laws for Neural Language Models

Reference 15

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source=pdf_text observed=2026-08-07T10:18:58.707015Z digest=sha256:056c22dce134ba046a9e3ca8662a6232f97909b37cef1cf4eae3c7ead4cead5b

Observation f1fcdd84-5312-4afb-8315-7520f2c4d706 · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Large Language Models are Zero-Shot Reasoners

Reference 16

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source=pdf_text observed=2026-08-07T10:18:58.865036Z digest=sha256:f381271d232c35132d357627190e3f14c09431c2bb337bc808ac1b4c9d61e7ae

Observation bd125714-1912-4bad-97dc-d4b7e6f6707f · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Efficient memory management for large language model serving with pagedattention

Reference 17

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source=pdf_text observed=2026-08-07T10:18:59.062833Z digest=sha256:c71b4d5bd700ceb9bf0cf49952a12e919bbebbdbadbf0d8bad3c111bde314b74

Observation 013f40b3-c033-419e-b65d-a3e2733194da · outbound

This paper cites S*: Test Time Scaling for Code Generation.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation S*: Test Time Scaling for Code Generation

Reference 18

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source=pdf_text observed=2026-08-07T10:18:59.138334Z digest=sha256:76215cca2ac33540205f9ba4e193242bdfcb58e95276c3d708c032d773114357

Observation 6abc88ac-b0a4-4e35-a369-ad7127b1d423 · outbound

This paper cites Verilogeval: Evaluating large language models for verilog code generation.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Verilogeval: Evaluating large language models for verilog code generation

Reference 19

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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=2026-08-07T10:18:59.244092Z digest=sha256:a652ecdb7a9dbae56be358309f299bb55a7b9053ee038f163c767ca54a4a253c

Observation ae946843-c748-4368-8668-7a43df3ceda5 · outbound

This paper cites CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair

Reference 20

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source=pdf_text observed=2026-08-07T10:18:59.351726Z digest=sha256:8aaa4bfaed9ad3ef2365e0efe8890b49c13da370ba4e4eedc21143fb714cfb69

Observation 64356431-e245-4fde-b30c-e086e908e01d · outbound

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

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Rtlcoder: Fully open-source and efficient llm-assisted rtl code generation technique

Reference 21

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raw_fallback, observed 2026-08-07T10:19:10.186835Z

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=2026-08-07T10:18:59.588468Z digest=sha256:7e8ec8db4e48e54240f348d7dd3a79f9d5bccad004881768561bbb405c5209f2

Observation 7d05f20e-b875-4654-a3cb-3d3e565dfab5 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation StarCoder 2 and The Stack v2: The Next Generation

Reference 22

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source=pdf_text observed=2026-08-07T10:18:59.814283Z digest=sha256:a6d19603c2b96ea7b418e305b54a9c70963d7d6528a06ef6cbe5c16bf669650a

Observation 3b468d12-d922-4a8e-8312-52e8b8f9686c · outbound

This paper cites Rtllm: An open-source benchmark for design rtl generation with large language model.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Rtllm: An open-source benchmark for design rtl generation with large language model

Reference 23

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:19:00.033141Z digest=sha256:4e99846057d4a9d00246e93e42dac02477ce8a26f0c4950a9f3260ac5dc7740a

Observation 7cf9fb04-820d-46e4-a53a-fd4c4ed2491f · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Self-Refine: Iterative Refinement with Self-Feedback

Reference 24

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source=pdf_text observed=2026-08-07T10:19:00.175157Z digest=sha256:086de23a77ce2a9bdab710ee6a796162f2cd3e17f2fbaebd6a79ba1912e609af

Observation 4b4951ca-5df6-4def-bad0-6f5a77a09e52 · outbound

This paper cites s1: Simple test-time scaling.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation s1: Simple test-time scaling

Reference 25

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source=pdf_text observed=2026-08-07T10:19:00.321791Z digest=sha256:c4bdfd6bf0b5d08d84a647a53ce9808a0aa6154fd108ef5b98c86a8808254edb

Observation dbc8a275-2870-4aa1-99f3-97f701307836 · outbound

This paper cites Gpt-3.5 models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Gpt-3.5 models

Reference 26

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raw_fallback, observed 2026-08-07T10:19:09.752108Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:19:00.492100Z digest=sha256:a09d067e5d061160163c40813b04330b0cd0eea2f3ef6e3c182fdf66d8ed704a

Observation 594a4331-9d66-4295-a72f-489abba25a20 · outbound

This paper cites GPT-4 Technical Report.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation GPT-4 Technical Report

Reference 27

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source=pdf_text observed=2026-08-07T10:19:00.649463Z digest=sha256:85c79d456d95deef9918a1c7222bb9079eb9686fb9490f1b363aa3631e1005a4

Observation 46619f58-befa-47df-8bf0-42e566178bfb · outbound

This paper cites BetterV: Controlled Verilog Generation with Discriminative Guidance.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation BetterV: Controlled Verilog Generation with Discriminative Guidance

Reference 28

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source=pdf_text observed=2026-08-07T10:19:00.756053Z digest=sha256:cc15044c5aa5f086a3b3d9d757955361215f5dec01cbc78a63619c01656b8f7a

Observation 97fe1ceb-f769-4b49-8555-ebf45d34707d · outbound

This paper cites Code Llama: Open Foundation Models for Code.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Code Llama: Open Foundation Models for Code

Reference 29

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source=pdf_text observed=2026-08-07T10:19:00.878974Z digest=sha256:aead81267a6dbb27f7723f2fea3e75c460996c2b40c4736fea0fdd49752dd6be

Observation c82ae771-28fb-4cad-909e-2798a63c63c5 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 30

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source=pdf_text observed=2026-08-07T10:19:01.015038Z digest=sha256:5cae1f017c8c7878655d450d6a07207ff1f123e63521249c4154442d1e94d810

Observation d4649ebf-4125-4746-9cc0-08b07efc5a65 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 31

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source=pdf_text observed=2026-08-07T10:19:01.197473Z digest=sha256:049ee64e413e5cb2e0011b1e7e80c6ddb5ee0d88df0e22d401b77d849c454db6

Observation 7d553c97-edc5-4c31-be44-01aa18b4d3da · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Magicoder: Empowering Code Generation with OSS-Instruct

Reference 32

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source=pdf_text observed=2026-08-07T10:19:01.376438Z digest=sha256:d72610f3625db0b4b841001131022d15dd7e120576dcbd7f62a58501ee5f6420

Observation ef8f7826-8e2a-4d0b-b299-6704f952b9a4 · outbound

This paper cites Mg-verilog: Multi-grained dataset towards enhanced llm-assisted verilog generation.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Mg-verilog: Multi-grained dataset towards enhanced llm-assisted verilog generation

Reference 33

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raw_fallback, observed 2026-08-07T10:19:09.563912Z

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=2026-08-07T10:19:01.625577Z digest=sha256:71ce838f776eae5c0c4162468db84f81c186d6f9e1c0f480da4e49c21afa9ea9

Observation 9344ee08-656b-4539-badc-d0506c4ad5ec · outbound

This paper cites CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization

Reference 34

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source=pdf_text observed=2026-08-07T10:19:01.791486Z digest=sha256:43828a10ef92e748867241f9c37bbec56f75ada6aeb022f148ee72078ddc0ec8

Observation efcfeecc-5bae-4786-84f6-0dacf2ebd3a3 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:19:01.930888Z digest=sha256:7e71df1982d64f7f859312f6584ccda5ba9053cd7d712c9342f58030c0e0be86

Observation 5fff743a-2e5b-4000-ae1b-13e15a1d031c · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:09.362605Z

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=2026-08-07T10:19:02.072693Z digest=sha256:28cdb7013bd90f3361619dc0fb0991fc0cec5201dd155e4b5016ec1d3ec72c59

Observation 8ee5bf07-b355-41de-942c-8a80d2e621dd · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:09.146654Z

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=2026-08-07T10:19:02.275573Z digest=sha256:2444ec62b81d30768fb232c2535e77e9bf09497770ab1f4f85e0d9f5532da878

Observation 6e2b4932-2c6a-47fd-aae4-af9deed5057b · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:08.923657Z

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=2026-08-07T10:19:02.467037Z digest=sha256:031972ff3416d4d87034e7aa9ea7b776ec7cb3d393fef42c701d0c0b2239e7ae

Observation c97b5402-7b27-4f72-b46e-95d05dca0e91 · outbound

This paper cites Here is an example: • Guidelines for the problem description format: The problem description section should be enclosed within <PROBLEM> </PROBLEM> tags.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Here is an example: • Guidelines for the problem description format: The problem description section should be enclosed within <PROBLEM> </PROBLEM> tags

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:08.679601Z

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=2026-08-07T10:19:02.654550Z digest=sha256:c629349733cce687b9b38ca2d561e0dcaaceaab2733e3926ea4afeb48e06886c

Observation 782021bb-02eb-4c91-a8e9-f6b997d36832 · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:08.464818Z

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=2026-08-07T10:19:02.927095Z digest=sha256:708f1459dafd099c28ea35257e14f55913097aec53c41cc7b5eafdae6a5ce4b8

Observation 4947ba01-9c36-4f39-8f2a-4be2993ce3bd · outbound

This paper cites If you do have a reset method that is synchronous to a clock, make sure to add the clock signal to the problem module input.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation If you do have a reset method that is synchronous to a clock, make sure to add the clock signal to the problem module input

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:08.276633Z

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=2026-08-07T10:19:03.076903Z digest=sha256:0e0347693b2db45e8315007655cf1b9f3fb7c40ae845ef20206c1b41c88eeb5a

Observation 4c66df16-ff35-49f6-8b68-163c200959ca · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:08.038364Z

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=2026-08-07T10:19:03.207039Z digest=sha256:b8527b395c3e3645e538cd863a61eec86a95d400d244bdd1cffd1c1526feb23e

Observation c184106a-222e-4bc9-8bc7-4150744384dc · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:07.837287Z

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=2026-08-07T10:19:03.389048Z digest=sha256:f1905c8c696e03efbabb4de9df901b373b850aeb9fa662458077b46a055f900a

Observation 58c2a5ed-779e-4e50-bbda-a7ab1559f6cd · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:07.618960Z

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=2026-08-07T10:19:03.567124Z digest=sha256:fc9494c2c41860dbf943e4a2a1d52a5a9f92dee3ca4c876054bc7e1f8b168629

Observation a4e72cce-7b1f-4c24-8114-146996b6d9aa · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:07.429594Z

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=2026-08-07T10:19:03.751026Z digest=sha256:ad0053c62d335ee285b422f719047acf14c24a3c2731a8734387d1623700c68f

Observation 3e0ca757-988b-4873-8568-2fcab3f7e8be · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:07.196455Z

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=2026-08-07T10:19:03.926613Z digest=sha256:01c6e70cf95e6e459037050072aef2bfb9d946f889605deec45b3117a0c3cfba

Observation 1291ff5d-53ae-4337-a906-3c594c00fd52 · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:07.027119Z

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=2026-08-07T10:19:04.082738Z digest=sha256:92f55bd5b2292566eef1cf657387dcd7d21626d1bc8ff4ee1d7f7939a744291a

Observation e0915c80-b274-44c8-ae6d-0f3662a4c94c · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:06.827543Z

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=2026-08-07T10:19:04.294628Z digest=sha256:2cdfb626ad836ed951028112e4b3e8f1525bf044331ef21b265119377a53af37

Observation 62205528-d15f-4689-a4b0-873280a92154 · outbound

This paper cites • Below shows an example: Problem description: Build a counter that counts from 0 to 999, inclusive, with a period of 1000 cycles.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation • Below shows an example: Problem description: Build a counter that counts from 0 to 999, inclusive, with a period of 1000 cycles

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:06.625079Z

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=2026-08-07T10:19:04.444025Z digest=sha256:6ffab58dc18a3da4b45d81522c1817d6c89ee4f8d520f9ea7ecfd8aea376cd26

Observation a13d2621-4311-4c5d-b352-2b0c930f959d · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:06.438541Z

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=2026-08-07T10:19:04.572501Z digest=sha256:115c1751b6ae8c83bd61e6d8113fcf2d20d64a82f451df1b069bb78145952c16

Observation ab85396e-5789-43cd-ad82-43f5b3b7a068 · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:06.209755Z

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=2026-08-07T10:19:04.727028Z digest=sha256:41e21469325e93e33be68252c63d5e83e766de03d78121cfdde80223390c768c

Observation 85311b94-c921-4418-b471-43e7101cd0cf · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:06.018299Z

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=2026-08-07T10:19:04.870525Z digest=sha256:1b46db9b3fb5b58b369bad829ea44d3d06b9f5b372a054c1aa0665023dd3d978

Observation 75af742b-01c9-4256-8fbe-78d3cb7ef758 · outbound

This paper cites an unresolved cited work.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:19:05.692194Z

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=2026-08-07T10:19:04.998158Z digest=sha256:d797bf099ac979efc441519ef094cf3b1ae83b925074cca02df5f8a9f7246ccf

Pith citing papers

Observation bff2fbcb-feab-4255-9080-484364914640 · inbound

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

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T00:31:00.525028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:31:00.525028Z digest=sha256:b1eb138f39084ee215ec987da617b0d6b941802cb62edad3f261585a65a06390

Observation c8740064-f8ff-4952-915a-68fbccb8163c · inbound

CASS-RTL: Correctness-Aware Subspace Steering for RTL Generation with LLMs cites this paper.

CASS-RTL: Correctness-Aware Subspace Steering for RTL Generation with LLMs ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:57:07.375327Z

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=2026-06-27T23:06:44.339563Z digest=sha256:bebcc1031465cd3d493c5ea2239c10328e24c355f80fb75a005fedd6d9283504

Observation e3a5b2d3-ecbf-4677-8490-a86ef3d33040 · inbound

LongRTL: Graph-Similarity-Guided LLM-driven Long Context RTL Optimization cites this paper.

LongRTL: Graph-Similarity-Guided LLM-driven Long Context RTL Optimization ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-03T03:37:35.794807Z

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=2026-06-27T15:02:42.299863Z digest=sha256:2dbca1014d98e56d0167ea66527628d6a39f2f5a154d7ab49c50487a2822c47a

Observation 3074b87c-f7ba-43d8-9c49-8bd85d3b1c07 · inbound

Agentic Hardware Design as Repository-Level Code Evolution cites this paper.

Agentic Hardware Design as Repository-Level Code Evolution ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-01T18:45:58.336486Z

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=2026-06-29T01:49:07.838897Z digest=sha256:6d4ee0605540f99246c80619da922e2301cc1e26a65f3cddcd545c0f6a2834bf

Observation 33850d85-f626-446a-932c-b76da9938d46 · inbound

A Progressive Approach to Synthesizable RTL Design Generation Using LLMs cites this paper.

A Progressive Approach to Synthesizable RTL Design Generation Using LLMs ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T15:14:08.913455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:14:08.913455Z digest=sha256:e1b1245d028bbea842e67416e6ee4218811f36f455498c8b34acac641ca4c79e

Observation 291e250f-f2ed-451d-925c-398b3074cd1c · inbound

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes cites this paper.

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T06:36:59.249142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:36:59.249142Z digest=sha256:6f6122794c3899daf2c50c54677cbf8acfe1013ec00f4e0e32acbf75e51eaa6b