Pith. sign in

Paper Citation Record · LEDGER

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2506.08029.

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

pith.paper-citation-record.v1
2506.08029 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:35.611307Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

30 of 30 outbound references displayed

  • verified exact1
  • verified fuzzy21
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37411ca0-f4d3-4321-8e86-1ba25c2efa4e · outbound

This paper cites Understanding the impact of entropy on policy optimization.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Understanding the impact of entropy on policy optimization

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.161962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.501753Z digest=sha256:b7a8fc14b2de98ef5084d59789fbb12846122e10c025ffd4e0d0f8d0147bb58c

Observation 6e6ead95-0b10-477a-9488-85039e9a4828 · outbound

This paper cites F., Jiang, Z., Zhu, K., Mirhoseini, A., Goldie, A., and Pan, D.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning F., Jiang, Z., Zhu, K., Mirhoseini, A., Goldie, A., and Pan, D

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.506723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.506723Z digest=sha256:0bf016b75ba8fbfe79297ac169f73703f5de7893c31a0b19ac92d8e19c87f210

Observation 5c3a3c5d-8759-488d-a091-46539364fdb6 · outbound

This paper cites Domain knowledge-infused deep learning for automated analog/radio-frequency circuit parameter optimization.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Domain knowledge-infused deep learning for automated analog/radio-frequency circuit parameter optimization

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.151862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.510720Z digest=sha256:fe46ac1b2295f49ce09971336c88a2e700b9677d38cd4aa2a83e2c8e2daaa28f

Observation 941f1ee7-9241-4e4f-bc8b-3aed322eea9e · outbound

This paper cites A new training approach for parametric modeling of microwave passive components using combined neural networks and transfer functions.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning A new training approach for parametric modeling of microwave passive components using combined neural networks and transfer functions

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.140031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.515440Z digest=sha256:6ae779c457f23cf2ad4c2fdb83835185a02ddf8f8adeed577e13b9d17bde19f3

Observation 33eefe95-36c9-4143-8db0-dd6dd6c91804 · outbound

This paper cites Characterization of the dissolution of water microdroplets in oil.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Characterization of the dissolution of water microdroplets in oil

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:52:35.806885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.519640Z digest=sha256:e0616c3213210d54335de24925b3c61f81396a4e4334fd297e51ba1dc3e01d5f

Observation 89cf8bcb-f2d0-4bc2-88f8-a63e99673a84 · outbound

This paper cites C., Rodriguez, D., Magaz, M.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning C., Rodriguez, D., Magaz, M

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.128938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.524015Z digest=sha256:580ea2f4d7a6a4d7a4ff4596321e7cb62d697a0549d6d51b416f18da03471847

Observation 67bd06c3-14e8-40e4-87a1-c8fa291c6f5a · outbound

This paper cites Ckt GNN : Circuit graph neural network for electronic design automation.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Ckt GNN : Circuit graph neural network for electronic design automation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.117164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.527855Z digest=sha256:3dfcf7c5729eb09d0c8021b24843e6bbafe08daa82f1ac8ea0394c557dc28b01

Observation 7197f87a-d5a7-4d7d-b2d2-47c615e054e4 · outbound

This paper cites Parametric modeling of microwave components using adjoint neural networks and pole-residue transfer functions with em sensitivity analysis.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Parametric modeling of microwave components using adjoint neural networks and pole-residue transfer functions with em sensitivity analysis

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.105260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.530929Z digest=sha256:041cc326a977f8b95ee34db71145fe686ea5daa44d1a5b3b96fde980bc2b8633

Observation aec84c03-1ffb-4296-8ebb-c689e22bbbb6 · outbound

This paper cites Erdse: efficient reinforcement learning based design space exploration method for cnn accelerator on resource limited platform.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Erdse: efficient reinforcement learning based design space exploration method for cnn accelerator on resource limited platform

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.094546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.533991Z digest=sha256:3f8bbd87530e683547ce8fbdea9eaf4a4874ad1adccd727929fd2305040a7a28

Observation 35f34c9f-0b65-40e8-949c-994b53edd24a · outbound

This paper cites Automated design and optimization of distributed filtering circuits via reinforcement learning, 2024.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Automated design and optimization of distributed filtering circuits via reinforcement learning, 2024

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.083570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.537105Z digest=sha256:68f794f3bc0486b05e267f9f1644b3398a865cda8763fd17c075488b04239c74

Observation f270a8b9-ce50-4c34-bcdc-8368a07b5563 · outbound

This paper cites Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.073330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.541196Z digest=sha256:e8bfa8b3cfd0b793a6c5776d1ebd773acdd6a48f59689503c79d114bab360e23

Observation 27a236ea-d656-4338-96ba-423c70b1227d · outbound

This paper cites an unresolved cited work.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:52:36.063095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.545140Z digest=sha256:2f63ce0cbdf486f69ebff09c6ac78a1780acefa0664437cb026f6f65dbce71a6

Observation 0a2fd7a1-7062-4b2f-a40f-9fcb9b1cc1b2 · outbound

This paper cites Microstrip Filters for RF/Microwave Applications.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Microstrip Filters for RF/Microwave Applications

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.051632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.549007Z digest=sha256:60cb8e35e713d75e8a05be4b83e411de20db6202efe57ee1f84e5235d9cbeaac

Observation 633006e5-b4cc-4918-856e-a2e8c9d5107a · outbound

This paper cites and Lancaster, M.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning and Lancaster, M

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.039415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.551911Z digest=sha256:9089f2ce00ccbda491af69a8de6db8b3025a84978b894589a1512f730facd506

Observation fb34228b-9a45-42b7-aca3-fc385ac9f6c7 · outbound

This paper cites Revisiting Design Choices in Proximal Policy Optimization.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Revisiting Design Choices in Proximal Policy Optimization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.555023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.555023Z digest=sha256:570aae7a8b2ac8bc18ba0949bdad3633e0915dd91586bd4f0e1ec8a8ba07a93c

Observation 01bf5d46-76a9-46d4-9eba-43930b0e73c1 · outbound

This paper cites M., Wang, S., Goldie, A., Mirhoseini, A., Jiang, J.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning M., Wang, S., Goldie, A., Mirhoseini, A., Jiang, J

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.028444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.558823Z digest=sha256:0e733159754de7937971dd83cb316b290b23372a55d0c57e458c6f736f127606

Observation 87374406-834c-4f52-945d-91a6680f1088 · outbound

This paper cites Design of microwave filters.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Design of microwave filters

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.018038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.562825Z digest=sha256:2cabbbece6a143cba79fa67458d075eb5c6f0bc13e63e3d575d25efc736d7b06

Observation 71bac582-01f2-406d-9cfe-1121daa476b1 · outbound

This paper cites and Horta, N.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning and Horta, N

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:36.006303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.565977Z digest=sha256:7940912a4bdd30e43b49ba315823abf891c384dcf53e3b0709f5183ef3d6519d

Observation fb2dac8d-4313-46ba-9d68-db57154f3a6c · outbound

This paper cites an unresolved cited work.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.569268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.569268Z digest=sha256:7dc294975e46c84bb3b4aa6e6f8e6bcf762fb4c13a69d0d14183521e2a115d64

Observation 0207cc8b-f9b1-472f-98a3-bb084d3268c2 · outbound

This paper cites an unresolved cited work.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.572383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.572383Z digest=sha256:85566359884ac8a4386ae6ad81c36cd255fc616fd0c215d401a73b9c88e80a85

Observation 7a382047-c8bb-4cc9-8257-cfe8eddcaf6a · outbound

This paper cites Batch B ayesian optimization via multi-objective acquisition ensemble for automated analog circuit design.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Batch B ayesian optimization via multi-objective acquisition ensemble for automated analog circuit design

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.994493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.576691Z digest=sha256:3f2e5b103a1472c47e0abb46d92b5ad25dac4ed916203b2d02e22c69b88a0c83

Observation ca0df640-61d2-4445-81d9-2905c3025b2b · outbound

This paper cites an unresolved cited work.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:52:35.981995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.580949Z digest=sha256:5e82aa4112e3493eabd1b514685e515e8483f4014429e647c7d5d3f9e5a586e7

Observation 492e4d16-918d-4d73-b925-54a5683fc840 · outbound

This paper cites V., Laudon, J., Ho, R., Carpenter, R., and Dean, J.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning V., Laudon, J., Ho, R., Carpenter, R., and Dean, J

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.970766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.584090Z digest=sha256:bf383e2d4c0f038aa4e53ba38f0b7c9c9228e880729806a4b5ff22f53b87cc85

Observation af62616a-efeb-462c-9121-48e2fa1b7485 · outbound

This paper cites S., Qin, T., and Yan, N.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning S., Qin, T., and Yan, N

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.959807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.587406Z digest=sha256:289b0c993432bf7e7b1bac61e1f1e0b70eb4bb5c90343c3ecd05965a4c1277a4

Observation 71859a72-35e9-45a8-9506-16407821aa96 · outbound

This paper cites Proximal policy optimization algorithms, 2017.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Proximal policy optimization algorithms, 2017

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.590998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.590998Z digest=sha256:5efe29803214e26cc01faee28f976641779f790fd48503421b2c54d5fb743b49

Observation 88959972-600c-4105-aeef-fcfd07cead41 · outbound

This paper cites Autockt: deep reinforcement learning of analog circuit designs.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Autockt: deep reinforcement learning of analog circuit designs

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.940370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.594302Z digest=sha256:65bd91af801af22403aace187192eb9486a332c457676d057f65f934a17fefa5

Observation d6250e67-49b5-47b4-98fe-b063bc41ae91 · outbound

This paper cites Gcn-rl circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Gcn-rl circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.927148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.598487Z digest=sha256:1b50ca92b9c57210fa4a6dc73c15099a4262fd0ebba01316ccdcfab59b09a2e3

Observation ce48e29a-171b-44f5-81df-10d12d3d383c · outbound

This paper cites Ironman-pro: Multiobjective design space exploration in hls via reinforcement learning and graph neural network-based modeling.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Ironman-pro: Multiobjective design space exploration in hls via reinforcement learning and graph neural network-based modeling

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.915481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.602203Z digest=sha256:5c304aedfa7d7ef196dcef2175400301c0de87cd72c4425a763c546d1f400b5e

Observation ccd64e1f-6d1d-4890-9007-5426e5cb5dcc · outbound

This paper cites Circuit- GNN : Graph neural networks for distributed circuit design.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning Circuit- GNN : Graph neural networks for distributed circuit design

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:52:35.902194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T11:52:35.606861Z digest=sha256:26ee80b4ba170b8b7fd5dd01a3671041c2ecdd94ba991ca25b00a028490de90e

Observation 6ecaaad4-f7b4-4c0b-80dc-71844fb5eea9 · outbound

This paper cites write newline.

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning write newline

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:35.611307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:52:35.611307Z digest=sha256:82b81226fa4ee2e1e67f6151abe0b9558f11051db45a7b4f621e4d85d360a543

Pith citing papers

No inbound Pith citation observations are available.