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Paper Citation Record · LEDGER

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

As of 21 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 6 inbound Pith citation observations for arXiv:2502.01681.

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

pith.paper-citation-record.v1
2502.01681 v3

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:13:54.054704Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:10:24.147369Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:51:17.775716Z

Reference resolution

21 of 21 outbound references displayed

  • verified exact2
  • verified fuzzy9
  • unresolved9
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cfdd21ec-90b4-4f87-bff5-19c27725502f · outbound

This paper cites Over-Squashing in Graph Neural Networks: A Comprehensive survey.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Over-Squashing in Graph Neural Networks: A Comprehensive survey

Reference 1

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local_arxiv, observed 2026-08-09T18:13:54.492186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 05043cf1-367c-41e7-9baf-ac6579fdafdd · outbound

This paper cites Results demonstrate that increasing k significantly impacts GPU memory usage.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Results demonstrate that increasing k significantly impacts GPU memory usage

Reference 4

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 54ca1607-4723-466f-a8af-7ace6623d98c · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Semi-Supervised Classification with Graph Convolutional Networks

Reference 8

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Observation 3748627a-24e2-4a5d-a797-58ebc228fb0d · outbound

This paper cites On eda-driven learning for sat solving.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale On eda-driven learning for sat solving

Reference 9

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raw_fallback, observed 2026-08-09T18:13:54.731149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T18:13:53.925845Z digest=sha256:02595d42ccf80e3fcac8aae8a13be413f0cf1ed686aeb6304848df05ee015506

Observation cb9e3fff-444a-4dc0-adbf-f4a67ee2213f · outbound

This paper cites Polargate: Breaking the functionality representation bottleneck of and-inverter graph neural network.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Polargate: Breaking the functionality representation bottleneck of and-inverter graph neural network

Reference 10

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raw_fallback, observed 2026-08-09T18:13:54.701487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation d984cb7e-7933-49fb-87da-d73f25103b9d · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale A Survey on Oversmoothing in Graph Neural Networks

Reference 13

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source=pdf_text observed=2026-08-09T18:13:53.955934Z digest=sha256:9165024831f6d7938ad05393e19ac710ffd06e8e2bf42700203e7a33bbcadc4d

Observation 9157501c-d524-4a0b-b55a-f6ac73e7a657 · outbound

This paper cites Deeptpi: Test point insertion with deep reinforcement learning.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Deeptpi: Test point insertion with deep reinforcement learning

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation cfc74427-c78f-4f55-870e-e66cb1b3e06a · outbound

This paper cites Deepgate2: Functionality-aware circuit representation learning.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Deepgate2: Functionality-aware circuit representation learning

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 84b8390e-b7d3-4ddc-9b0e-b0c69f76ebf1 · outbound

This paper cites Logic Optimization Meets SAT: A Novel Framework for Circuit-SAT Solving.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Logic Optimization Meets SAT: A Novel Framework for Circuit-SAT Solving

Reference 16

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Observation fd6728c0-3ec4-471e-a1c9-a4a8f1db79a4 · outbound

This paper cites Graph Attention Networks.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Graph Attention Networks

Reference 17

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Observation d837f1a4-5a3a-4164-8012-bf366b6fa4c9 · outbound

This paper cites Gamora: Graph learning based symbolic reasoning for large-scale boolean networks.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Gamora: Graph learning based symbolic reasoning for large-scale boolean networks

Reference 18

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raw_fallback, observed 2026-08-09T18:13:54.610398Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 75814cec-362c-45a6-ad0e-92902949a0fc · outbound

This paper cites To dis- entangle the functional and structural embeddings, we design training tasks with distinct labels to supervise each component.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale To dis- entangle the functional and structural embeddings, we design training tasks with distinct labels to supervise each component

Reference 19

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raw_fallback, observed 2026-08-09T18:13:54.579870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation f909e25e-0006-4450-a140-a6190de16533 · outbound

This paper cites Case Name ad44 f20 ab18 ac1 ad14 Avg.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Case Name ad44 f20 ab18 ac1 ad14 Avg

Reference 21

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raw_fallback, observed 2026-08-09T18:13:54.521472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 5c397035-610d-4446-ae3a-4ab4ffc0c240 · outbound

This paper cites NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs

Reference 1997

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Observation 38097846-62f6-4f08-9da6-6ab34ac551ac · outbound

This paper cites High Fidelity Neural Audio Compression.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale High Fidelity Neural Audio Compression

Reference 1999

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source=pdf_text observed=2026-08-09T18:13:53.893409Z digest=sha256:81f95a12cf4c40f9b4bf4e9215311b1de933f26ee4564e2b2fda29a065b4e373

Observation 90cc8d6d-80fc-4928-a600-242770005bdf · outbound

This paper cites Abc: An academic industrial-strength verification tool.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Abc: An academic industrial-strength verification tool

Reference 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e96c063b-dae2-40a7-a437-7d683097d105 · outbound

This paper cites DeepSeq: Deep Sequential Circuit Learning.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale DeepSeq: Deep Sequential Circuit Learning

Reference 2017

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local_arxiv, observed 2026-08-09T18:13:54.317902Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-09T18:13:53.907538Z digest=sha256:c52ced0f7cf63c07107fa23b6f582b7a38ced5cbaf2a97a64363c6f714b065bf

Observation 1fefa84f-651d-449d-b3fd-b9cfe2a110cd · outbound

This paper cites an unresolved cited work.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Unresolved cited work

Reference 2019

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 2989387f-c450-4383-898d-f90daff86047 · outbound

This paper cites Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits

Reference 2022

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source=pdf_text observed=2026-08-09T18:13:53.900532Z digest=sha256:560bb8a2a860fa75af37fdcdf19c26fa8b6a0c2ceb1d04efcdd9fbc36731a409

Observation ebd85b15-f47b-4a2a-be5f-b94df10de0e0 · outbound

This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 2023

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Observation 3f6b55b1-455d-4d31-82fb-b64d202328b6 · outbound

This paper cites GraphiT: Encoding Graph Structure in Transformers.

DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale GraphiT: Encoding Graph Structure in Transformers

Reference 2024

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source=pdf_text observed=2026-08-09T18:13:53.938803Z digest=sha256:cfc77428c8c4f2bcfe392e565444a1317fd25655a8bbaed13a55db39d3b9bf86

Pith citing papers

Observation bd2e7ba8-c6b0-44bc-85ad-d40557d44431 · inbound

DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning cites this paper.

DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 19

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source=pdf_text observed=2026-08-09T10:59:38.182095Z digest=sha256:2a0b2b90a4e37b5dd9b8ec8660fd4f704adb911e0e6393f8ba7e47573d5fe5aa

Observation e282a060-3555-43dd-b6a8-56e261e3b454 · inbound

DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining cites this paper.

DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 20

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source=pdf_text observed=2026-08-07T23:14:10.222152Z digest=sha256:062306b83fd20a737ed8445ef31c7fd66abd4ac30a7c1f1c7030d50b796eb81d

Observation 23be3cb8-a27e-4a30-9456-6a15081e9472 · inbound

ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA cites this paper.

ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 29

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Observation bf6167ff-96be-4d75-88cb-07bd972987c8 · inbound

MMCircuitEval: A Comprehensive Multimodal Circuit-Focused Benchmark for Evaluating LLMs cites this paper.

MMCircuitEval: A Comprehensive Multimodal Circuit-Focused Benchmark for Evaluating LLMs DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 14

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local_arxiv, observed 2026-08-06T15:51:17.782618Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e179754a-cd89-4249-bf7d-642859f73bd1 · inbound

TRACE: Learning to Compute on Circuit Graphs cites this paper.

TRACE: Learning to Compute on Circuit Graphs DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 40

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source=arxiv_source observed=2026-08-15T15:49:54.877371Z digest=sha256:6c201de17152dfab389f7b85d974b2db09e5da8d391a394c0597946682b98555

Observation c1c0cbbc-3ade-4db2-be4f-62cc71467bd2 · inbound

BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement cites this paper.

BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale

Reference 90

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