Pith. sign in

Paper Citation Record · LEDGER

RTL++: Graph-enhanced LLM for RTL Code Generation

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 11 inbound Pith citation observations for arXiv:2505.13479.

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

pith.paper-citation-record.v1
2505.13479 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:36:25.257526Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:40:15.702642Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T03:56:34.651017Z

Reference resolution

44 of 44 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77ab3b03-1b8b-4bed-b088-49ea7fe3e3d0 · outbound

This paper cites an unresolved cited work.

RTL++: Graph-enhanced LLM for RTL Code Generation Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:36:26.030459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.051373Z digest=sha256:b2ae8c2ed75fd6b09e3356347ff91975c22613f65ec47f7c3783e3b6926cfebf

Observation 601957e1-000f-4088-9f59-9227f37daab2 · outbound

This paper cites Language Models are Few-Shot Learners.

RTL++: Graph-enhanced LLM for RTL Code Generation Language Models are Few-Shot Learners

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.056804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.056804Z digest=sha256:775c119cb69a205db3031d60e6b7c94afc440a5ce96f4cafba629264a4b582c8

Observation ae9f7461-ce0e-474e-b60e-6ea129a40c45 · outbound

This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

RTL++: Graph-enhanced LLM for RTL Code Generation CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.062017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.062017Z digest=sha256:c379bcc13ca1fe32cf727d1863f1c0d4741ba8919ac0b5444474ccb4d984c34d

Observation 55998e7f-d39a-4c93-9dd8-a192d6067b00 · outbound

This paper cites Evaluating large language models trained on code,.

RTL++: Graph-enhanced LLM for RTL Code Generation Evaluating large language models trained on code,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.066843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.066843Z digest=sha256:7c72810a0ed3458a4189ecf18e87cd26c70ef95554b02f5562f6a6be63fe2b74

Observation 6be11f3a-62dc-421b-a322-c5784d94c2d7 · outbound

This paper cites Competition-level code generation with alphacode,.

RTL++: Graph-enhanced LLM for RTL Code Generation Competition-level code generation with alphacode,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.076264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.076264Z digest=sha256:7d88ff083caf674ff3aa42d369a6f2da235f034d4fa8ccb87eab404d3c1799f4

Observation 98ed9788-4c22-483d-8c86-06199167d0c4 · outbound

This paper cites PaLM 2 Technical Report.

RTL++: Graph-enhanced LLM for RTL Code Generation PaLM 2 Technical Report

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.081195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.081195Z digest=sha256:8492cdc89b6870dc6f63ad9efac3d7c22ef8484f4cce85e8f1d14c81bf044145

Observation 23d6a493-ba50-4819-898c-2d8c935c8288 · outbound

This paper cites Claude: An ai assistant built by anthropic,.

RTL++: Graph-enhanced LLM for RTL Code Generation Claude: An ai assistant built by anthropic,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:26.004097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.086031Z digest=sha256:20677c9dafed6b4504d6b969a82e15cd5a29b96dc78215256e6848802e8b10e0

Observation 98c79d38-bc6e-4606-8756-18247cb13ca8 · outbound

This paper cites OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection.

RTL++: Graph-enhanced LLM for RTL Code Generation OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.090851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.090851Z digest=sha256:4557e9702e05e2efc9f3a6b5c566353d97cffd4b01e6b4793bb6eeb0b7f710bc

Observation 0ac9745d-f12d-48c7-8cf0-c0754edf5484 · outbound

This paper cites Simeval: Investigating the similarity obstacle in llm-based hardware code generation,.

RTL++: Graph-enhanced LLM for RTL Code Generation Simeval: Investigating the similarity obstacle in llm-based hardware code generation,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.095907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.095907Z digest=sha256:18c09cdb9bb783ad7e7286208afe65d89ebfb1dd78f9d4d5d9168ede7315f623

Observation aaf6f6ca-410b-45b4-bcae-3968e507b2f6 · outbound

This paper cites Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,.

RTL++: Graph-enhanced LLM for RTL Code Generation Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.987890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.101160Z digest=sha256:eee910ea543a1e1d7290c2ffaf20f6c766ee1fcc081bab040bd580c1930046a4

Observation 689978e1-1bc9-4a04-aa1a-3280d9e17181 · outbound

This paper cites LLM-IFT: LLM-Powered Information Flow Tracking for Secure Hardware.

RTL++: Graph-enhanced LLM for RTL Code Generation LLM-IFT: LLM-Powered Information Flow Tracking for Secure Hardware

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.106057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.106057Z digest=sha256:0c1e59de449818e6363f491f637e122a2d96e3c6da898d0d4ab907db4f0a5840

Observation 95477ae3-0a13-49c5-810a-fb95b949ea99 · outbound

This paper cites Self-hwdebug: Automation of llm self-instructing for hardware security verification,.

RTL++: Graph-enhanced LLM for RTL Code Generation Self-hwdebug: Automation of llm self-instructing for hardware security verification,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.973221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.110797Z digest=sha256:8ee9a8783e356b49155090e793406ac6b5e1b3b560001c6459052d545813029a

Observation eee68966-9aa9-447d-b17e-52e73cd5d596 · outbound

This paper cites Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models,.

RTL++: Graph-enhanced LLM for RTL Code Generation Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.958588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.115377Z digest=sha256:a3b9d89586180eb10f0e207b495a38be64ae126e19bc435681609f575c90830c

Observation a02be447-db27-4fc4-84b2-62540e9bd02f · outbound

This paper cites Evolutionary large language models for hardware security: A comparative survey,.

RTL++: Graph-enhanced LLM for RTL Code Generation Evolutionary large language models for hardware security: A comparative survey,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.943498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.119664Z digest=sha256:9ca8776ddcbb2ab65b2b5be0c633e9d60a746ee1c563de12f9ae59b6494dec82

Observation e3d0a2eb-df63-425d-a350-a62d35ea0ad6 · outbound

This paper cites VeriGen: A Large Language Model for Verilog Code Generation.

RTL++: Graph-enhanced LLM for RTL Code Generation VeriGen: A Large Language Model for Verilog Code Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.123920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.123920Z digest=sha256:61d0ebce3a4f977c53a906ed61ee3abff1e10267073b19a0802b1d26dc2ca362

Observation e6d5a876-ea64-400d-b6e9-b201a5ba5048 · outbound

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

RTL++: Graph-enhanced LLM for RTL Code Generation BetterV: Controlled Verilog Generation with Discriminative Guidance

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.128493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.128493Z digest=sha256:dcc159a248d9ade5fe976011d161e065ddcd514d50e529bb62038cc7cac0cf7d

Observation 77c14e65-df97-4d60-a528-14ad3aef5f53 · outbound

This paper cites AutoVCoder: A Systematic Framework for Automated Verilog Code Generation using LLMs.

RTL++: Graph-enhanced LLM for RTL Code Generation AutoVCoder: A Systematic Framework for Automated Verilog Code Generation using LLMs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.133349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.133349Z digest=sha256:43952f57f1b753060d0ad86a8e6b9ff7b05eb4ecbebca886fd734dc51f579b22

Observation 93b73ae5-1fb0-494b-ad83-cc189df9f6aa · 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.

RTL++: Graph-enhanced LLM for 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 18

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.138342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.138342Z digest=sha256:df4551df8962a32d277d3dc40e43bc66061c277432a610dc7641aae2e8cc20af

Observation 0b8d7427-da3a-496b-86ca-6bb24e9f957e · outbound

This paper cites Let your graph do the talking: Encoding structured data for llms,.

RTL++: Graph-enhanced LLM for RTL Code Generation Let your graph do the talking: Encoding structured data for llms,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.928221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.143084Z digest=sha256:3ecc8fa54ab5f8263bf65ed6653a63588aa8a16abb827ebea48074f268b3f8fd

Observation fdad7cc0-dec5-4d78-952e-675ff912e41c · outbound

This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

RTL++: Graph-enhanced LLM for RTL Code Generation REALM: Retrieval-Augmented Language Model Pre-Training

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.147304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.147304Z digest=sha256:3097b47b4c83bd318135e70953be31e7a98b1be64fa193796cdec85a2e224dc0

Observation 88c1a8e4-ee73-48ff-b71a-2b30d8b3e16c · outbound

This paper cites Graphllm: Boosting graph reasoning ability of large language model,.

RTL++: Graph-enhanced LLM for RTL Code Generation Graphllm: Boosting graph reasoning ability of large language model,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.912310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.156448Z digest=sha256:17a15dbeea46a39540943deed637004e50d3153b9f25fdb636457ba04e65015b

Observation 47cc33c8-2624-44ca-b4aa-746a40bc1dc7 · outbound

This paper cites G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering.

RTL++: Graph-enhanced LLM for RTL Code Generation G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.160965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.160965Z digest=sha256:c534e39a9551d8c51dd112317a5b2c2771c2552c3663e21bf7ff17ff9c1ed7de

Observation 87bf4140-9d89-427a-895c-9e58d3cdfed5 · outbound

This paper cites Talk like a Graph: Encoding Graphs for Large Language Models.

RTL++: Graph-enhanced LLM for RTL Code Generation Talk like a Graph: Encoding Graphs for Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.165625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.165625Z digest=sha256:fa4fdd079e239c2a5a51aabfd2972fb9455a0f7c8010e7c5e43f4efab1cb63de

Observation 9ed00215-cc97-4008-91b1-f3c84a173b2e · outbound

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

RTL++: Graph-enhanced LLM for RTL Code Generation CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.170036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.170036Z digest=sha256:a96944f47f9c505a8a4b71e812bca0b83afbfc93fb1c6e4c8c6f0258f491a45e

Observation bf4d0259-9c38-4104-9530-139bf18e52e7 · outbound

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

RTL++: Graph-enhanced LLM for RTL Code Generation ChipNeMo: Domain-Adapted LLMs for Chip Design

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.174737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.174737Z digest=sha256:73214aa2fa0244f4d55b4bb6e2e5d12b185a797dd5505497519afc3c62a52666

Observation b452a824-98ff-4768-96d3-7a60c464cabe · outbound

This paper cites Data is all you need: Finetuning llms for chip design via an automated design-data augmentation framework,.

RTL++: Graph-enhanced LLM for RTL Code Generation Data is all you need: Finetuning llms for chip design via an automated design-data augmentation framework,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.179403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.179403Z digest=sha256:0e1567981140b67a6e2079dee090497d8876c4caffedb2637af3a6f6bab93d9a

Observation 03acc1df-d7ed-4f31-933c-51e29b9225da · outbound

This paper cites Chateda: A large language model powered autonomous agent for eda,.

RTL++: Graph-enhanced LLM for RTL Code Generation Chateda: A large language model powered autonomous agent for eda,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.896951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.183663Z digest=sha256:4a8802cac297d7078d475830ecc6d001471bab9b88c81664f25dbf9bb74b8b43

Observation 933c9b33-f281-4cfe-91c3-2400b8f9ab6a · outbound

This paper cites MAGE: A Multi-Agent Engine for Automated RTL Code Generation.

RTL++: Graph-enhanced LLM for RTL Code Generation MAGE: A Multi-Agent Engine for Automated RTL Code Generation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.187870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.187870Z digest=sha256:620746cf99fd26ef2d720c55383a5f1b8a7efee6142946e3e04b728712dad48d

Observation 76f5b5e0-d301-40f9-a547-3ea939dbb492 · outbound

This paper cites CodeGraph: Enhancing Graph Reasoning of LLMs with Code.

RTL++: Graph-enhanced LLM for RTL Code Generation CodeGraph: Enhancing Graph Reasoning of LLMs with Code

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.192466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.192466Z digest=sha256:54132bbf78ba83a655f9d8a7739284fc714f6cbb5b8288fc6ba6e10f773aa66c

Observation 494a654b-63b5-486f-b366-2ce34cae114a · outbound

This paper cites Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning.

RTL++: Graph-enhanced LLM for RTL Code Generation Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.197214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.197214Z digest=sha256:7ff32b18798a8cfb273af5156adf8c2e5c78243f1b7a7e889d0cbe2339f4e7e1

Observation a98db5ba-769e-4874-8269-0d5d522aeb0f · outbound

This paper cites Graphinstruct: Empowering large language models with graph understanding and reasoning capability,.

RTL++: Graph-enhanced LLM for RTL Code Generation Graphinstruct: Empowering large language models with graph understanding and reasoning capability,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.202146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.202146Z digest=sha256:f158c02a8ab5e04b878d2eaea8e0b1d2a9dd331d8c9acb533316c15f4afd74e6

Observation 1675e897-4d64-448c-adff-7c42379a155d · outbound

This paper cites Graph convolutional networks in language and vision: A survey,.

RTL++: Graph-enhanced LLM for RTL Code Generation Graph convolutional networks in language and vision: A survey,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.882159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.206529Z digest=sha256:9d01fe8ff5f4187e92e18bc3990cae42eb71235465e201af4fae5bf78ac93538

Observation 449d4efe-f528-41f9-99fc-8e30d12c546f · outbound

This paper cites Yosys-a free verilog synthesis suite,.

RTL++: Graph-enhanced LLM for RTL Code Generation Yosys-a free verilog synthesis suite,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.867131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.211041Z digest=sha256:13597e9f9e5273b143f2adb7e9fd761e311188aee2cb64dc310921f0e4ced5a8

Observation 45059ab3-9e57-47fa-9ca0-d877d5204682 · outbound

This paper cites Bounded model checking using satisfiability solving,.

RTL++: Graph-enhanced LLM for RTL Code Generation Bounded model checking using satisfiability solving,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.852780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.215592Z digest=sha256:ab0d25235f931ab69e686d4c452b6524adcb393760f634d7663b0b4826a48a05

Observation a53fcd06-17ca-49c4-addf-58b1f679a22a · outbound

This paper cites A Survey on In-context Learning.

RTL++: Graph-enhanced LLM for RTL Code Generation A Survey on In-context Learning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.220093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.220093Z digest=sha256:6c526554cf50c6cdd1be3c134503c235fd07b10969b34ad047242fe7aa3864cf

Observation 40b96f99-4b3f-4429-bd69-7c81f734e511 · outbound

This paper cites Code llama: Open foundation models for code,.

RTL++: Graph-enhanced LLM for RTL Code Generation Code llama: Open foundation models for code,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.225074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.225074Z digest=sha256:e0d6f0a6f249706df2787f6b561dfcba69f2d1582f3619feb772ff9c1f7791d7

Observation c0364602-f2d4-4f3b-8b12-db9a1112934d · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

RTL++: Graph-enhanced LLM for RTL Code Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.234178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.234178Z digest=sha256:ca14e6e3c227966a50eb62111157fe8c121e539a97910f79cb10a848e005e57e

Observation d8dfd050-846a-47ef-ba7e-0c72023f9b2c · outbound

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

RTL++: Graph-enhanced LLM for RTL Code Generation Verilogeval: Evaluating large language models for verilog code generation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.828836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.238717Z digest=sha256:ebc9cffbcf66f0abf96a76d7cad822746768def18dcd7dc33e33d73d3204d0a5

Observation bc2bd669-6eae-4e00-a971-420dcf719735 · outbound

This paper cites Revisiting VerilogEval: A Year of Improvements in Large-Language Models for Hardware Code Generation.

RTL++: Graph-enhanced LLM for RTL Code Generation Revisiting VerilogEval: A Year of Improvements in Large-Language Models for Hardware Code Generation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.243134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.243134Z digest=sha256:fade9446f496a1d68ed14159519c7b7aab6ac617105a166448f66ff1994c84ed

Observation b9485870-131b-4930-9d3b-df4425eefedb · outbound

This paper cites RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model.

RTL++: Graph-enhanced LLM for RTL Code Generation RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.247836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.247836Z digest=sha256:7e2b26e78d28c3c3531975bd2b89ef09e167516d112eefcb18b39a951ab07201

Observation 57551b17-a087-42bc-9669-f648b3006de4 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

RTL++: Graph-enhanced LLM for RTL Code Generation Lora: Low-rank adaptation of large language models,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:36:25.813453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:36:25.253039Z digest=sha256:b6e2279225322f86481012c958895ac960341c810edfce675f8159dd86f802ef

Observation b2f96b1d-3458-4688-96eb-5eb925e0d5e8 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

RTL++: Graph-enhanced LLM for RTL Code Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.257526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.257526Z digest=sha256:18c7c1bdb7d6e26355054bc87d9ed155e4e634734974536fc1da32459a51622e

Observation aa522e1c-04af-43c3-98a8-dd17a067003c · outbound

This paper cites Evaluating Large Language Models Trained on Code.

RTL++: Graph-enhanced LLM for RTL Code Generation Evaluating Large Language Models Trained on Code

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.071440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.071440Z digest=sha256:8311808a31ccc3377fc7f8c75f18ee07ed3122156973bd0bc4c82c5927c87bce

Observation 35dd602a-305e-427d-b76d-82c5128ba94a · outbound

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

RTL++: Graph-enhanced LLM for RTL Code Generation Code Llama: Open Foundation Models for Code

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T22:36:25.229454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:36:25.229454Z digest=sha256:d2312121de62034e4f539adf084f4ad295b49b3a0726bd1757fe7258737f7ef1

Pith citing papers

Observation 4002d0c8-0195-4812-8013-d651e65399ab · inbound

DecoRTL: A Run-time Decoding Framework for RTL Code Generation with LLMs cites this paper.

DecoRTL: A Run-time Decoding Framework for RTL Code Generation with LLMs RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T20:40:15.702642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:40:15.702642Z digest=sha256:626f17c3e6d8bac95e24fa19598ddc254b95554d49aaef179a7d0ae25ebcf0ec

Observation a10dbe5d-33bc-403b-998a-2880c8229865 · inbound

VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation cites this paper.

VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T18:54:01.135603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:54:01.135603Z digest=sha256:88dae1a812526c445c13eaa0a87e6be9adc397eecb5d89208d01d60822eed82d

Observation 8b659837-5d7c-425a-b77b-784d77b459ee · inbound

TimelyHLS: LLM-Based Timing-Aware and Architecture-Specific FPGA HLS Optimization cites this paper.

TimelyHLS: LLM-Based Timing-Aware and Architecture-Specific FPGA HLS Optimization RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T14:42:04.944107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:42:04.944107Z digest=sha256:635b8846fdf8c9ce89f0b240c09cd4f250bac0458f42d71a0ae4d1a9196a4f91

Observation 2eb52469-5d7d-4b55-9785-aa958f9f930f · inbound

MACO: A Multi-Agent LLM Framework for Automated CGRA Hardware/Software Co-Design cites this paper.

MACO: A Multi-Agent LLM Framework for Automated CGRA Hardware/Software Co-Design RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T16:31:32.475251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:31:32.475251Z digest=sha256:50c05073092d8feba8fceb46c72c1f9ac10616aef688a41df71c7c44253e0b21

Observation 869a73da-f650-42f6-adc5-dd29e74dada0 · inbound

SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation cites this paper.

SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:36:26.580465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-07T10:16:07.200458Z digest=sha256:3db9a306a6c13562c8c54b4ab8e3ca476d5dd92d9d1b8f62ad5794fc52b76eef

Observation f7252fa3-7c8f-4a3b-9413-0748c382302e · inbound

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

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:51:26.667352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T03:57:51.577486Z digest=sha256:70e42664453a0492d8c5075157da0f4c38931fb0f6ed41772c80ea32562ecfbc

Observation 9c57c413-e0d6-4b1b-b415-aff54724ac05 · inbound

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

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:12:58.759395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T21:12:08.821202Z digest=sha256:883796de9ef697a668dc6ed5a9e928f5c383f078b68a46487690b85411d52c07

Observation e5fdfad5-b8e3-4cdd-96f1-3dade813bfc6 · inbound

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

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:59:55.406683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-21T08:58:25.469021Z digest=sha256:3a653e33efd64fcbc3db0fa581e4b96cd364d9913834706de6b1130d2bb417b3

Observation ad2ac106-b284-4f5e-b59c-cbc1727a34a0 · inbound

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

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:46.819888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T22:18:09.663488Z digest=sha256:46a9995c90cb5873b344c654c0d9e1d0b4314dde23a37a018a3623dd2ebf8029

Observation 90f07db2-e68c-4961-8395-62e1347ff294 · inbound

StepPRM-RTL: Stepwise Process-Reward Guided LLM Fine-Tuning for Enhanced RTL Synthesis cites this paper.

StepPRM-RTL: Stepwise Process-Reward Guided LLM Fine-Tuning for Enhanced RTL Synthesis RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-02T03:56:34.652684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T09:35:34.571333Z digest=sha256:0e526a2f88ccd44e7d82827d571db650c6fd5cf96f92c5b45583ec9c2e682c6c

Observation c255d8b9-0d72-447b-8e95-137867ab2117 · inbound

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

Hardware Design and Security in the Era of Chiplets and LLMs RTL++: Graph-enhanced LLM for RTL Code Generation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T10:13:18.224348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:13:18.224348Z digest=sha256:3d735169efc125ac1b193e80f355994a09cae537579765bf441831b10b5e9ed3