Pith. sign in

Paper Citation Record · LEDGER

AiEDA: Agentic AI Design Framework for Digital ASIC System Design

As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2412.09745.

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

pith.paper-citation-record.v1
2412.09745 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:50:14.751120Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T12:38:45.687975Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:46:20.456407Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9b56091d-dd58-4dc8-af78-02b1f8e9c84b · outbound

This paper cites Introduction to large language models (llms),.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Introduction to large language models (llms),

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.193010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.623570Z digest=sha256:c6c32f70e1fb4f68953119492d7d8a4561b543b504ba28130eef91cf281149d4

Observation 92be4852-5d6e-45e5-84fb-0c5c560f407b · outbound

This paper cites Openroad: Toward a self-driving, open-source digital layout implementation tool chain,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Openroad: Toward a self-driving, open-source digital layout implementation tool chain,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.169794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.632381Z digest=sha256:621a0c7d6bfd8f61288a7b6cc2338957b377ac01971a05aad57dda24b3826f2d

Observation f892e6b0-e2d6-4d4c-8b35-6e45c44fd05d · outbound

This paper cites Exploring agentic workflows: The power of ai-agent collaboration,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Exploring agentic workflows: The power of ai-agent collaboration,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.146885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.638905Z digest=sha256:276dfac16e12956ae535ba2e646b0a4aac090fe2ff0fb538bc2f11a74df4491c

Observation 7cc3fe29-3034-44fb-a207-3309c763e574 · outbound

This paper cites Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.651241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.651241Z digest=sha256:c9f726454c6ccacbeb5f822ea8831c2cd9f23d272a15102b881ddec9bff1d5e0

Observation 5b5d33bd-e95a-4893-b435-baed545bfa9c · outbound

This paper cites Dave: Deriving automatically verilog from english,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Dave: Deriving automatically verilog from english,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.127249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.661647Z digest=sha256:8579557334192714c0ec2ad3aa23202b37a77e58fd0ce7f31251c0d0fc9dc3e2

Observation e5fdfb5a-038d-43aa-a0b3-69f5dad1e6d3 · outbound

This paper cites Verigen: A large language model for verilog code generation,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Verigen: A large language model for verilog code generation,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.678121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.678121Z digest=sha256:99e458f77e2bd8bfa5f3e979167f762a52969c271efb1c0fb3b4e13a079d9f40

Observation 658c4514-8baa-4bd5-91b8-e4ec9f3c2d3a · outbound

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

AiEDA: Agentic AI Design Framework for Digital ASIC System Design ChipNeMo: Domain-Adapted LLMs for Chip Design

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.685619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.685619Z digest=sha256:8d04214ac0f41738dd52ceadfdf198c55c0f034f7b9db0399dad63fb80489b5f

Observation 6baacd1a-89df-4495-8481-37763c42c676 · outbound

This paper cites MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.694942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.694942Z digest=sha256:a84c2b75b1b9ec6606064d32ca0248a216ab615fd734877b3eb04c83cb8c8e31

Observation d3dca82d-0830-4b36-95df-a38f3807728e · outbound

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

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.701648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.701648Z digest=sha256:d2d10539f5aa0ea865b97faa5b0b8be0d88158563731db55f9a1de700cefe2f8

Observation 513c2a44-7ed9-4065-999c-65f34399f050 · outbound

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

AiEDA: Agentic AI Design Framework for Digital ASIC System Design AutoChip: Automating HDL Generation Using LLM Feedback

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T16:50:14.707534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:50:14.707534Z digest=sha256:a898259d8fe6b1f8723fae1954e8839bfbedab6f110f6e4be6a494c9be7ee49f

Observation c3ca7e95-4fe5-412d-9936-6850ac3ec4e5 · outbound

This paper cites Toward an open-source digital flow: First learnings from the openroad project,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Toward an open-source digital flow: First learnings from the openroad project,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.081077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.716842Z digest=sha256:bb15e432f1ccc911e78529e298aaeff24fdc6c6d4ec758e5190d67ddc4c772c5

Observation 01f65ea9-7d8b-4fc8-85d5-73e510061939 · outbound

This paper cites 0.08mm2 128nw mfcc engine for ultra-low power, always-on smart sensing applications,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design 0.08mm2 128nw mfcc engine for ultra-low power, always-on smart sensing applications,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.051959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.722769Z digest=sha256:6f4c2a199d1d9763d3a5c4ab0e4f853d6bb8076094357342f64a54c2c58d6742

Observation 2d71b2dd-4c07-4d41-a6ac-280e7427930f · outbound

This paper cites An efficient mfcc extraction method in speech recognition,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design An efficient mfcc extraction method in speech recognition,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:15.023568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.728838Z digest=sha256:b155f4b44673ed47b3dfdd5e5d3476d5bc7092a607b018ec357d0309b26efbf5

Observation 68b5f8f0-2cb9-459f-887c-0cbf36d7a97e · outbound

This paper cites Speech recognition based on convolutional neural networks and mfcc algorithm,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Speech recognition based on convolutional neural networks and mfcc algorithm,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:14.994390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.744085Z digest=sha256:4cf2f23cdaf494a010bd0807d64708ec26c5177736d677e3d663d9c81bf16f16

Observation fd56fa1d-b52f-4e87-8eda-18f129be1799 · outbound

This paper cites Langgraph: Build resilient language agents as graphs,.

AiEDA: Agentic AI Design Framework for Digital ASIC System Design Langgraph: Build resilient language agents as graphs,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T16:50:14.965859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T16:50:14.751120Z digest=sha256:8a8a5d608a24a3c4cf265244942e4b276650e100c021af362ef3253251a8a613

Pith citing papers

Observation c625280d-8c81-4029-818b-262661235439 · inbound

TensorLift: Automatic Extraction of Tensor-Level ISA Semantics from Accelerator RTL via MLIR Semantic Lifting cites this paper.

TensorLift: Automatic Extraction of Tensor-Level ISA Semantics from Accelerator RTL via MLIR Semantic Lifting AiEDA: Agentic AI Design Framework for Digital ASIC System Design

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:46:20.478358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T12:38:45.687975Z digest=sha256:6b631bb457d86abfbaf48bb34ae2d4c172e4367bea87c6b41d977f4a1a7bfdea