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Paper Citation Record · LEDGER

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment

As of 23 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.03193.

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

pith.paper-citation-record.v1
2607.03193 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:14:43.579131Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 8a1d4fe6-d200-49c0-87d8-f533a02ba130 · outbound

This paper cites Yu, Jay Gambetta, A.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Yu, Jay Gambetta, A

Reference 1

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Observation b09738b4-98cc-4c59-b436-37466c981680 · outbound

This paper cites Grimsmo, S.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Grimsmo, S

Reference 2

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Observation 09ce83f5-b5ff-4b9b-8184-9256afd6aed5 · outbound

This paper cites Orlando, Simon Gustavsson, and William D.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Orlando, Simon Gustavsson, and William D

Reference 3

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Observation bc31b17c-3982-4054-b37f-1323bb637ec1 · outbound

This paper cites Motzoi, J.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Motzoi, J

Reference 4

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Observation 6f3ea694-d620-4880-a768-0ca9da55365a · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 5

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Observation 328887f9-9f14-49a3-b14e-2a8cbe0a8411 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 6

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Observation cd60ebc7-c72d-4b32-aa30-68eb17a8cae9 · outbound

This paper cites Cross, Lev S.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Cross, Lev S

Reference 7

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verified exact
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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 92776cad-8d31-436a-b650-bf7d48ed16a6 · outbound

This paper cites Isakov, Vadim N.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Isakov, Vadim N

Reference 8

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Observation ae8c89ed-93f8-4f3d-a958-ba4a642195e2 · outbound

This paper cites Bardin, Rami Barends, et al.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Bardin, Rami Barends, et al

Reference 9

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Observation 492e35ea-aaff-481d-b9dc-2a99093b3da1 · outbound

This paper cites Quality, Speed, and Scale: three key attributes to measure the performance of near-term quantum computers.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Quality, Speed, and Scale: three key attributes to measure the performance of near-term quantum computers

Reference 10

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Observation 8f8720c3-f08f-4f76-9f56-0a6aba6e4cda · outbound

This paper cites Egger, Stefan Filipp, Frank K.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Egger, Stefan Filipp, Frank K

Reference 11

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Observation dd840118-a0a6-4f34-8611-06f69942a955 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 12

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Observation 500f5035-89d8-4cbc-826a-0310e0f18363 · outbound

This paper cites Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent

Reference 13

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Observation ba1b1432-2785-411d-aae9-f20a4bd919ca · outbound

This paper cites QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Reference 14

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Observation 876f75dd-e778-4e0e-b8c6-21d49f7c165c · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment ReAct: Synergizing reasoning and acting in language models

Reference 15

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Observation 775a3ac8-170f-4edc-8e83-aa9e8ae4f800 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 16

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Observation 9f3245ec-38d0-46ef-ab4a-fa14ca7b7b05 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Toolformer: Language models can teach themselves to use tools

Reference 17

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Observation 4af87f71-31e3-4546-8b27-68d961d0588d · outbound

This paper cites Patil, Tianjun Zhang, Xin Wang, and Joseph E.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Patil, Tianjun Zhang, Xin Wang, and Joseph E

Reference 18

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Observation 34b33d78-40e8-49ce-ace2-8f9006e47166 · outbound

This paper cites ToolLLM: Facilitating large language models to master 16000+ real-world APIs.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment ToolLLM: Facilitating large language models to master 16000+ real-world APIs

Reference 19

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Observation 795af38f-d36f-46ea-8514-0cc6a958028e · outbound

This paper cites Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D

Reference 20

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Observation a2e7b032-e810-47f1-8080-50259486347e · outbound

This paper cites Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes

Reference 21

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Observation 8e2c6831-bbf7-4a18-9759-478b22ceaf2c · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 2a1bd633-4814-45fb-8165-b13862771710 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 23

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Observation 701ec72c-da57-459e-ae9f-dae08b299f12 · outbound

This paper cites scqubits: a Python package for superconducting qubits.Quantum, 5:583,.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment scqubits: a Python package for superconducting qubits.Quantum, 5:583,

Reference 24

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Observation 1d8d7795-4cd4-4521-a58c-4ddb803340d4 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 25

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Observation e96422fe-bc1a-42d7-b42d-aaf2f298c24e · outbound

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Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 26

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Observation f37abdbf-e756-48d0-a894-5e82d6a702fe · outbound

This paper cites Digital Predistortion for Flux Control of Tunable Superconducting Qubits.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Digital Predistortion for Flux Control of Tunable Superconducting Qubits

Reference 27

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Observation 76c44d3b-073c-45f5-9626-967bea178584 · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 28

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Observation ecf72c25-c48d-43bf-9571-f901d69382ed · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 29

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Observation cc122f0a-3da2-44c4-8353-b68c768b91d0 · outbound

This paper cites Ithier, E.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Ithier, E

Reference 30

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Observation ace00196-c706-489b-9fdd-c9cac7ca32ab · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Reflexion: Language agents with verbal reinforcement learning

Reference 31

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Observation e0128331-0b4c-4eaf-a539-d63c947bcf7e · outbound

This paper cites an unresolved cited work.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Unresolved cited work

Reference 32

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Observation 7703737b-e6d7-4035-90eb-f4f35940a1b9 · outbound

This paper cites Optimizing generative AI by backpropagating language model feedback.Nature, 639:609–616, 2025.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Optimizing generative AI by backpropagating language model feedback.Nature, 639:609–616, 2025

Reference 33

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Observation 7da49d77-2d1d-463a-ae75-cb6af22685a6 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment Gemini: A Family of Highly Capable Multimodal Models

Reference 34

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Pith citing papers

No inbound Pith citation observations are available.