Paper Citation Record · LEDGER

TRACE: Learning to Compute on Circuit Graphs

As of 17 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2509.21886.

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

pith.paper-citation-record.v1
2509.21886 v3

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:49:54.895308Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact3
verified fuzzy16
unresolved24
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 202382c4-6d34-4a72-b519-04809eecb67d · outbound

This paper cites Iwls 2005 benchmarks.

TRACE: Learning to Compute on Circuit Graphs Iwls 2005 benchmarks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.690881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 034800e0-796f-4eab-b8c8-0281221502d7 · outbound

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

TRACE: Learning to Compute on Circuit Graphs On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.730207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec43e429-ba2a-4d83-aa8f-db6274347cca · outbound

This paper cites Btor2 , btormc and boolector3.0.

TRACE: Learning to Compute on Circuit Graphs Btor2 , btormc and boolector3.0

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.679991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 830d51ad-f2ec-4d9c-b337-7408877a7582 · outbound

This paper cites Notes on the iscas'89 benchmark circuits.

TRACE: Learning to Compute on Circuit Graphs Notes on the iscas'89 benchmark circuits

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.667812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e854485b-6ec0-451a-b0d6-abd03f31d96b · outbound

This paper cites Large circuit models: opportunities and challenges.

TRACE: Learning to Compute on Circuit Graphs Large circuit models: opportunities and challenges

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.657460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 880d741d-ec62-4c53-876d-8d2f0bc4867a · outbound

This paper cites Rt-level itc'99 benchmarks and first atpg results.

TRACE: Learning to Compute on Circuit Graphs Rt-level itc'99 benchmarks and first atpg results

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.647387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5f6f1b85-5cf1-484e-8cd9-81e532ce5486 · outbound

This paper cites Less is more: Hop-wise graph attention for scalable and generalizable learning on circuits.

TRACE: Learning to Compute on Circuit Graphs Less is more: Hop-wise graph attention for scalable and generalizable learning on circuits

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.636730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b9c58603-a957-455e-a781-382984dc2075 · outbound

This paper cites NetTAG: A Multimodal RTL-and-Layout-Aligned Netlist Foundation Model via Text-Attributed Graph.

TRACE: Learning to Compute on Circuit Graphs NetTAG: A Multimodal RTL-and-Layout-Aligned Netlist Foundation Model via Text-Attributed Graph

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:49:55.459819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 33e207a6-6f6e-49d4-ae3f-2df8f4be29c1 · outbound

This paper cites CircuitFusion: Multimodal Circuit Representation Learning for Agile Chip Design.

TRACE: Learning to Compute on Circuit Graphs CircuitFusion: Multimodal Circuit Representation Learning for Agile Chip Design

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.757833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ff79e94-655d-42bf-8e6d-a068ad7c5a18 · outbound

This paper cites A self-supervised, pre-trained, and cross-stage-aligned circuit encoder provides a foundation for various design tasks.

TRACE: Learning to Compute on Circuit Graphs A self-supervised, pre-trained, and cross-stage-aligned circuit encoder provides a foundation for various design tasks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.625077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b80435e-2e83-4e4e-b34a-b5ecb45363b3 · outbound

This paper cites Neural message passing for quantum chemistry.

TRACE: Learning to Compute on Circuit Graphs Neural message passing for quantum chemistry

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.764868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8acb5829-2d0a-42d6-b922-e08b2ce33a53 · outbound

This paper cites Inductive representation learning on large graphs.

TRACE: Learning to Compute on Circuit Graphs Inductive representation learning on large graphs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.768419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 815b2665-da5f-45d9-a596-e3450e877783 · outbound

This paper cites Deepseq2: Enhanced sequential circuit learning with disentangled representations.

TRACE: Learning to Compute on Circuit Graphs Deepseq2: Enhanced sequential circuit learning with disentangled representations

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.602617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a2085d99-46ff-402e-84b1-e1b7c6174e85 · outbound

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

TRACE: Learning to Compute on Circuit Graphs Semi-Supervised Classification with Graph Convolutional Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.775895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52a4f7f9-689d-4991-a503-53bd90d0d188 · outbound

This paper cites Deepgate: Learning neural representations of logic gates.

TRACE: Learning to Compute on Circuit Graphs Deepgate: Learning neural representations of logic gates

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.591781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5fb624f5-ee17-47c3-90a3-d2fead522dec · outbound

This paper cites Deeper insights into graph convolutional networks for semi-supervised learning.

TRACE: Learning to Compute on Circuit Graphs Deeper insights into graph convolutional networks for semi-supervised learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.580933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4010f224-6c10-435b-834f-7fbc66597163 · outbound

This paper cites DeepCircuitX: A Comprehensive Repository-Level Dataset for RTL Code Understanding, Generation, and PPA Analysis.

TRACE: Learning to Compute on Circuit Graphs DeepCircuitX: A Comprehensive Repository-Level Dataset for RTL Code Understanding, Generation, and PPA Analysis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.791838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bb3cee0-9bee-4d7e-adfb-de723142e3bb · outbound

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

TRACE: Learning to Compute on Circuit Graphs Polargate: Breaking the functionality representation bottleneck of and-inverter graph neural network

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.569191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14a0f3ed-2ecc-479a-a3a4-2060a61ad7e2 · outbound

This paper cites Ithemal: Accurate, portable and fast basic block throughput estimation using deep neural networks.

TRACE: Learning to Compute on Circuit Graphs Ithemal: Accurate, portable and fast basic block throughput estimation using deep neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.558009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5d37cf39-c994-4443-80b9-fd09d053833d · outbound

This paper cites Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, Will Hang, Emre Tuncer, Quoc V.

TRACE: Learning to Compute on Circuit Graphs Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, Will Hang, Emre Tuncer, Quoc V

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.548060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b5c3ed3e-b152-4225-bc07-1a53930cab1e · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

TRACE: Learning to Compute on Circuit Graphs Representation Learning with Contrastive Predictive Coding

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.806592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fd0b319-2614-46dc-b322-365737ff6678 · outbound

This paper cites Recipe for a general, powerful, scalable graph transformer.

TRACE: Learning to Compute on Circuit Graphs Recipe for a general, powerful, scalable graph transformer

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.810188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569eb5ad-5fc4-4c82-b5e7-9c2f0ee13b10 · outbound

This paper cites Learning a SAT Solver from Single-Bit Supervision.

TRACE: Learning to Compute on Circuit Graphs Learning a SAT Solver from Single-Bit Supervision

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.814153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d412aa6-262b-4def-a904-89a1e0555095 · outbound

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

TRACE: Learning to Compute on Circuit Graphs Deepgate2: Functionality-aware circuit representation learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.531687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 15fe2906-d76c-4a93-95fa-1292b605dc33 · outbound

This paper cites DeepGate3: Towards Scalable Circuit Representation Learning.

TRACE: Learning to Compute on Circuit Graphs DeepGate3: Towards Scalable Circuit Representation Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.821843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 702447d1-3711-4dbc-9dbe-dcc52b7d9067 · outbound

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

TRACE: Learning to Compute on Circuit Graphs ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.825555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ee0ab12-6cfe-4a59-a7ff-9ca1ab82448e · outbound

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

TRACE: Learning to Compute on Circuit Graphs DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:49:55.319811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 456e20c1-d88a-4600-83df-da7ba64812a5 · outbound

This paper cites Graph Attention Networks.

TRACE: Learning to Compute on Circuit Graphs Graph Attention Networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.833333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9238b82-c7c5-43c8-a714-eec09342e08d · outbound

This paper cites Fgnn2: A powerful pre-training framework for learning the logic functionality of circuits.

TRACE: Learning to Compute on Circuit Graphs Fgnn2: A powerful pre-training framework for learning the logic functionality of circuits

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.837672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a39d8c94-26b1-447f-8de1-ce5b79494103 · outbound

This paper cites Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment.

TRACE: Learning to Compute on Circuit Graphs Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:49:55.295884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2db7126c-1aa0-4d16-9280-5b904405fcdf · outbound

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

TRACE: Learning to Compute on Circuit Graphs Gamora: Graph learning based symbolic reasoning for large-scale boolean networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.514790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8eb50d34-9a4a-4a86-a95a-8898b3dffb53 · outbound

This paper cites DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion.

TRACE: Learning to Compute on Circuit Graphs DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.849790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9e21cd6-d190-4121-9017-7b0e94ae6871 · outbound

This paper cites Sgformer: Simplifying and empowering transformers for large-graph representations.

TRACE: Learning to Compute on Circuit Graphs Sgformer: Simplifying and empowering transformers for large-graph representations

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:49:55.503804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c00ae8d4-7eb5-4bc6-b845-8df5b9cf7740 · outbound

This paper cites Preplacement net length and timing estimation by customized graph neural network.

TRACE: Learning to Compute on Circuit Graphs Preplacement net length and timing estimation by customized graph neural network

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.857936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ba8aa7-2bfd-4149-8aaf-64a4ac498b59 · outbound

This paper cites How Powerful are Graph Neural Networks?.

TRACE: Learning to Compute on Circuit Graphs How Powerful are Graph Neural Networks?

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.862302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c9e32f9-238d-4d6f-8513-9e17a3d57975 · outbound

This paper cites Revisiting semi-supervised learning with graph embeddings.

TRACE: Learning to Compute on Circuit Graphs Revisiting semi-supervised learning with graph embeddings

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.865942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fea3b9b0-99ea-4800-b43a-d9fe2a731e38 · outbound

This paper cites Jiang, Luca Amarú, Alan Mishchenko, and Robert Brayton.

TRACE: Learning to Compute on Circuit Graphs Jiang, Luca Amarú, Alan Mishchenko, and Robert Brayton

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.869466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e586337-7551-4364-a532-f651d31123ed · outbound

This paper cites Grannite: Graph neural network inference for transferable power estimation.

TRACE: Learning to Compute on Circuit Graphs Grannite: Graph neural network inference for transferable power estimation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.873289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale.

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

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.877371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38b08067-35be-4c10-bd3c-4288857a99bd · outbound

This paper cites Rl-mul: Multiplier design optimization with deep reinforcement learning.

TRACE: Learning to Compute on Circuit Graphs Rl-mul: Multiplier design optimization with deep reinforcement learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.880867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3f7d647-4e88-4bee-b557-5b7ea80b125e · outbound

This paper cites write newline.

TRACE: Learning to Compute on Circuit Graphs write newline

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.884048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c73b6a18-7f1e-444d-8174-01428c784b99 · outbound

This paper cites @esa (Ref.

TRACE: Learning to Compute on Circuit Graphs @esa (Ref

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.887861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8090e765-812c-4150-8559-a789d2cc6c83 · outbound

This paper cites an unresolved cited work.

TRACE: Learning to Compute on Circuit Graphs Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:54.891824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 477c15ef-795e-46d8-a63d-46d7481fb062 · outbound

This paper cites Yet, the dominant paradigm is architecturally mismatched for this task.

TRACE: Learning to Compute on Circuit Graphs Yet, the dominant paradigm is architecturally mismatched for this task

Reference 45

Resolution: malformed identifier; no resolver link, observed 2026-08-15T15:49:54.895308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.