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Paper Citation Record · LEDGER

ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.18770.

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

pith.paper-citation-record.v1
2406.18770 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:06:05.751257Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

37
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 866f1f5b-8fc0-4043-bd39-09c532704db0 · inbound

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits cites this paper.

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T17:06:05.751257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:06:05.751257Z digest=sha256:ff1be17994454525fb06a404fa8b33779045b6217b00683b46932d13e718d93e

Observation 7d8ce8dd-6fe2-49c2-bb16-c8841576b78d · inbound

Schemato -- An LLM for Netlist-to-Schematic Conversion cites this paper.

Schemato -- An LLM for Netlist-to-Schematic Conversion ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T15:49:40.381650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:49:40.381650Z digest=sha256:df9084caf642bbb30a8b5d9105020179d4e00540760b6c12e99c1ee590c0f692

Observation 02b948e2-f960-4423-964a-0126f6005cb3 · inbound

A Survey of Research in Large Language Models for Electronic Design Automation cites this paper.

A Survey of Research in Large Language Models for Electronic Design Automation ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T19:49:55.729628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:49:55.729628Z digest=sha256:8026e115f9ed991a6f8130473034d677e6d01eed5f6da717e5538a7c6c83582c

Observation 707e208a-8693-4f80-baa0-b69d180ab7b5 · inbound

A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction cites this paper.

A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:46.564750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:21:46.564750Z digest=sha256:beb1f51e8282b9d28baba7a7e541e3677ba859452db1d750b9c0cc9b50026635

Observation 560cc790-00c5-4231-b863-28da141ff656 · inbound

DiffCkt: A Diffusion Model-Based Hybrid Neural Network Framework for Automatic Transistor-Level Generation of Analog Circuits cites this paper.

DiffCkt: A Diffusion Model-Based Hybrid Neural Network Framework for Automatic Transistor-Level Generation of Analog Circuits ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T21:21:13.446164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:21:13.446164Z digest=sha256:0806c43220c3b93a76fb3f1c5a796d2b9df9cfc2b86d97c08e88e92fc12a7c5e

Observation d27bd3ff-95ff-4c89-adaa-2b89e480e302 · inbound

White-Box Reasoning: Synergizing LLM Strategy and gm/Id Data for Automated Analog Circuit Design cites this paper.

White-Box Reasoning: Synergizing LLM Strategy and gm/Id Data for Automated Analog Circuit Design ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T22:36:53.054573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:36:53.054573Z digest=sha256:d2450a5b4bbcf44a5b4ee759ae9e5972c38c5ba22c961295bc7c5caf47cea768

Observation 565e45a5-2741-42e1-98c4-6bd98e32389a · inbound

SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows cites this paper.

SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-07-12T00:38:26.341759Z

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=2026-07-12T00:33:59.659330Z digest=sha256:7af35d942b075ab9970b47f592d0a24bc1f32558015f9418117a39219a5a573b