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Paper Citation Record · LEDGER

StructuredRAG: JSON Response Formatting with Large Language Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2408.11061.

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

pith.paper-citation-record.v1
2408.11061 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:22:29.954377Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 35d336ff-8071-459b-b569-e865e999d667 · inbound

Universal and Context-Independent Triggers for Precise Control of LLM Outputs cites this paper.

Universal and Context-Independent Triggers for Precise Control of LLM Outputs StructuredRAG: JSON Response Formatting with Large Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T15:00:14.206962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:00:14.206962Z digest=sha256:ae42703dd4a7842c05bd286de55d414657898b1fd3f50aa60d1495c7d50a88ba

Observation 798f9f3c-a278-4412-89b3-b9ffda15226d · inbound

CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning cites this paper.

CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning StructuredRAG: JSON Response Formatting with Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T13:19:06.994409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:19:06.994409Z digest=sha256:4a08589f47751e56fe9d1f5a8b91eb608dde3a8f18f1f3382d4dc3bc1dd91539

Observation 7a43803c-c023-4f8c-a036-e3576bc2aca1 · inbound

Evaluating Language Models as Synthetic Data Generators cites this paper.

Evaluating Language Models as Synthetic Data Generators StructuredRAG: JSON Response Formatting with Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T22:17:42.726829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:17:42.726829Z digest=sha256:680ff8eb2df2df38af21b5216191b52d35ef57a157bb1d96a6f3a27e83ad2cbb

Observation 832fda25-a923-42f2-ac78-64a05f15037b · inbound

Querying Databases with Function Calling cites this paper.

Querying Databases with Function Calling StructuredRAG: JSON Response Formatting with Large Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T15:25:14.691850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.691850Z digest=sha256:4ed0c69ba8927913b7230ac040c029cc38d8b36fb299e26e31055e0535e1b1b0

Observation 8a82ec51-4a75-4049-9785-8ca355850fbe · inbound

LLM-KG-Bench 3.0: A Compass for SemanticTechnology Capabilities in the Ocean of LLMs cites this paper.

LLM-KG-Bench 3.0: A Compass for SemanticTechnology Capabilities in the Ocean of LLMs StructuredRAG: JSON Response Formatting with Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T20:22:29.954377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:22:29.954377Z digest=sha256:a825d3eb72e153db7ef99fd78af3ec1c6a8e588710d043362b488637b80cb701

Observation 17aabedd-20ac-4e00-ac31-4e4ae146a4c2 · inbound

How do Scaling Laws Apply to Knowledge Graph Engineering Tasks? The Impact of Model Size on Large Language Model Performance cites this paper.

How do Scaling Laws Apply to Knowledge Graph Engineering Tasks? The Impact of Model Size on Large Language Model Performance StructuredRAG: JSON Response Formatting with Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:07:00.551297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:07:00.551297Z digest=sha256:feef55e5b0f7b669943b7f17ad37119dc83229410966506c9ae9fbfb507dd3b9

Observation 6f6e5ba7-34f1-495d-a6ab-f056e6a6a825 · inbound

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models cites this paper.

Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models StructuredRAG: JSON Response Formatting with Large Language Models

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T21:37:56.940962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:37:56.940962Z digest=sha256:4a475759ff91dab8505c7ca3d07c27d564413f0d8cb2b6a9d00f2a91c7c14aae

Observation 5b93278d-902d-48b7-a844-849647f3add0 · inbound

OASBuilder: Generating OpenAPI Specifications from Online API Documentation with Large Language Models cites this paper.

OASBuilder: Generating OpenAPI Specifications from Online API Documentation with Large Language Models StructuredRAG: JSON Response Formatting with Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:06.621226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:38:06.621226Z digest=sha256:5f52362da1a31fdc7767b2115ff20f3a58d8910f7b1d93b3d5c6bf021030f3b4

Observation 2681144d-be27-4ec2-9346-bf4175310e8e · inbound

REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once cites this paper.

REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once StructuredRAG: JSON Response Formatting with Large Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T17:35:31.623431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:35:31.623431Z digest=sha256:29978611700401241163a8074714b182fc72dc2f00d23103a1ba36d385a2c128

Observation fcdb59f6-cd59-4811-b015-76bcf4da18a5 · inbound

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity cites this paper.

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity StructuredRAG: JSON Response Formatting with Large Language Models

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-18T17:11:39.122133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-18T17:10:57.875842Z digest=sha256:562760da2e117f07ca6631ca53a2ccab680d2effa482134cc1ddb29d00ace26a

Observation 3b69f33a-f7cd-4984-824c-4b5751bb92e3 · inbound

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity cites this paper.

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity StructuredRAG: JSON Response Formatting with Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T16:08:38.341580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:08:38.341580Z digest=sha256:e94f800a80d1be46603cfe96202d302c3222235b4273135cbb49e1ccdcbe6a54

Observation 92deaa59-dd6f-4bb5-aa89-a96553a250ed · inbound

End-to-end PDDL Planning with Hardcoded and Dynamic Agents cites this paper.

End-to-end PDDL Planning with Hardcoded and Dynamic Agents StructuredRAG: JSON Response Formatting with Large Language Models

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T23:38:41.694585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-16T23:34:20.411940Z digest=sha256:5f511ca58794089bb0344d3ffb06221f8c1fec717547dd6dd496c0a0b2d3cc5b

Observation cddeeff6-3dce-42cc-9be4-087c1b99b476 · inbound

Chinese Essay Rhetoric Recognition Using LoRA, In-context Learning and Model Ensemble cites this paper.

Chinese Essay Rhetoric Recognition Using LoRA, In-context Learning and Model Ensemble StructuredRAG: JSON Response Formatting with Large Language Models

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T01:18:26.883866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T01:13:56.010721Z digest=sha256:5338290fbda1544f2902614d175f795d11c455a04b8e72afc19c3ea693dec6fa

Observation 18a38d8a-8c97-4b0e-813a-73cc2c6d80be · inbound

Diagnosing CFG Interpretation in LLMs cites this paper.

Diagnosing CFG Interpretation in LLMs StructuredRAG: JSON Response Formatting with Large Language Models

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T00:24:46.753538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-10T00:24:09.265532Z digest=sha256:eb3deda67e8ad6db268937dc39f181d071dad6fbcbddb2b3f81bf2a119204b7c

Observation e84ae9db-4989-4fa0-9b7c-efa250c64ce0 · inbound

Implicit Framing in Obstetric Counseling Notes: A Grounded LLM Pipeline on a VBAC-Eligible Cohort cites this paper.

Implicit Framing in Obstetric Counseling Notes: A Grounded LLM Pipeline on a VBAC-Eligible Cohort StructuredRAG: JSON Response Formatting with Large Language Models

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:36:13.427472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T11:34:37.790650Z digest=sha256:b8a31a9f777de350b08af2191cf68f79a0e2095dd3ea7b6d4167b2a6f8e1d812

Observation e4b917c6-d1af-4810-85c1-116d7b61166d · inbound

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows cites this paper.

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows StructuredRAG: JSON Response Formatting with Large Language Models

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T05:15:04.037774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T05:10:18.822143Z digest=sha256:8218b1ce5a82208d5e42cc93a3335e18c3c8cafb4bf5a3582274f0fdf1f4a9be

Observation 04d95790-60e1-4be4-b5ef-26082db93d86 · inbound

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows cites this paper.

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows StructuredRAG: JSON Response Formatting with Large Language Models

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T14:25:47.072308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T21:19:09.033331Z digest=sha256:bcdb82cef3f80907a92f7d870e077df2b0ff48af6bc21e0be7ec9c1f7e42cd89

Observation 8f4a5d02-5d35-4dde-a9be-95f4001aa8d6 · inbound

Empirical Study for Structured Output Control in LLMs for Software Engineering cites this paper.

Empirical Study for Structured Output Control in LLMs for Software Engineering StructuredRAG: JSON Response Formatting with Large Language Models

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T02:47:37.507521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T15:42:28.064820Z digest=sha256:0a9ee30f038ea6b658a27c3588ac5dc25d83e031b5550e26cc03e45e88256937

Observation d3c29408-b2dd-4720-83fd-1caaaf57618a · inbound

AI Prototyper: A Figma Plugin for Decomposition-Based GUI Prototyping with LLMs cites this paper.

AI Prototyper: A Figma Plugin for Decomposition-Based GUI Prototyping with LLMs StructuredRAG: JSON Response Formatting with Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T00:57:42.083453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:57:42.083453Z digest=sha256:f3deea6fa4845741055111ce4269a696adca74617c6b8eb86531be16b01a5cba