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Paper Citation Record · LEDGER

Representing Prompting Patterns with PDL: Compliance Agent Case Study

As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2507.06396.

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

pith.paper-citation-record.v1
2507.06396 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:09:55.024301Z

measured 21 of 21 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

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b6b91be-d877-4ec7-bb3d-24a6aa243384 · outbound

This paper cites write newline.

Representing Prompting Patterns with PDL: Compliance Agent Case Study write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:54.924681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:54.924681Z digest=sha256:b3ba6689a4c27b68f5e8a9ef1aa7ad29ac10b82076381c5a9d58d354e36281a1

Observation d4008108-a7fc-41a7-b8f9-1184e09be96b · outbound

This paper cites LiteLLM , July 2025.

Representing Prompting Patterns with PDL: Compliance Agent Case Study LiteLLM , July 2025

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.561461Z

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=2026-08-06T19:09:54.928563Z digest=sha256:89a240dbaf78c9e6bda10df0a3762b9f0d5d5533292bdd5be3120c53f5ac6647

Observation c7bcde13-d36d-4153-865a-fad7d6aae29d · outbound

This paper cites Prompting is programming: A query language for large language models.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Prompting is programming: A query language for large language models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.549614Z

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=2026-08-06T19:09:54.931924Z digest=sha256:86043fdad77a3ccae5f4818d408b7cbf286f9bb6350b3165f26f42d277f48de2

Observation 5ecaaff6-f825-430f-8557-a12f86ab2782 · outbound

This paper cites an unresolved cited work.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:09:55.538479Z

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=2026-08-06T19:09:54.936017Z digest=sha256:ca60921eded78f28613713bebc54abc693e6cf9851c0e1044bcdd52d40566a99

Observation 47df0a6d-9680-4a0f-b142-3ddf63fc9e9c · outbound

This paper cites an unresolved cited work.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:09:55.526791Z

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=2026-08-06T19:09:54.939483Z digest=sha256:428cfe7f861ab216dda98a9d1ddb8c656f7d2e6cbfea070bbcdebfc52ca266a7

Observation 09144daa-df83-4281-b3bf-7ec592b03740 · outbound

This paper cites V., Haq, S., Sharma, A., Joshi, T.

Representing Prompting Patterns with PDL: Compliance Agent Case Study V., Haq, S., Sharma, A., Joshi, T

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.515349Z

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=2026-08-06T19:09:54.942846Z digest=sha256:2579a3d544b0a9f258cc325cd8542f3ecf7a70dd51c979272a8aae9e7465a84e

Observation a2afae97-5249-4027-95ab-c89a57b7bd1f · outbound

This paper cites an unresolved cited work.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:09:55.504163Z

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=2026-08-06T19:09:54.946722Z digest=sha256:1ce59cf15a9c20ce20f9633026871a94ac71ec5b10c62f8c16920ff8f3938e8f

Observation 63856d38-74ea-4f77-b273-ccea65800dc5 · outbound

This paper cites Llama Stack , July 2025.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Llama Stack , July 2025

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.492349Z

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=2026-08-06T19:09:54.950408Z digest=sha256:8bfb71cdd3d4c837e991a526a29145479f9ed472dc5df820e925c3ddc8540572

Observation 76ed587e-ff7c-49d0-8950-516728ed4f2b · outbound

This paper cites \ guidance\ : A guidance language for controlling large language models, July 2025.

Representing Prompting Patterns with PDL: Compliance Agent Case Study \ guidance\ : A guidance language for controlling large language models, July 2025

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.480529Z

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=2026-08-06T19:09:54.953496Z digest=sha256:bc5079a65a4ea7e314ac4429f9d8023eafa514074486c5c1c0523af9e259e19e

Observation 23e6fb8b-5b91-4457-bff7-d58e7ba8f8fb · outbound

This paper cites CrewAI : Framework for orchestrating role-playing, autonomous AI agents, July 2025.

Representing Prompting Patterns with PDL: Compliance Agent Case Study CrewAI : Framework for orchestrating role-playing, autonomous AI agents, July 2025

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.468399Z

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=2026-08-06T19:09:54.957828Z digest=sha256:6ac4cb4bc611fd444d1e9034e4f75141c695d81ba328822c79342920d0b0530f

Observation 8bfc16b7-634b-4eb2-b4d4-ef49cedabd80 · outbound

This paper cites L., Suarez, F., Ugarte, M., and Vrgo c , D.

Representing Prompting Patterns with PDL: Compliance Agent Case Study L., Suarez, F., Ugarte, M., and Vrgo c , D

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.455436Z

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=2026-08-06T19:09:54.961337Z digest=sha256:b75e8a394473fd7c5c300040ae485c7f59f3886ab4130d65730f561fd6074401

Observation 98c37564-ced8-4ee3-a564-ea3826c24054 · outbound

This paper cites and Zhang, B.

Representing Prompting Patterns with PDL: Compliance Agent Case Study and Zhang, B

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.439924Z

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=2026-08-06T19:09:54.964560Z digest=sha256:7ab7755de90fc105bf43725d2198fcca5055421ead5e1414b510bcae39bd6fc8

Observation 834af8cb-fca4-4540-8b4e-fea8ff6d914c · outbound

This paper cites AutoPDL : Automatic prompt optimization for LLM agents.

Representing Prompting Patterns with PDL: Compliance Agent Case Study AutoPDL : Automatic prompt optimization for LLM agents

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.247992Z

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=2026-08-06T19:09:54.969811Z digest=sha256:2dc167ee9f60a43e68937314215f1c3d32dfb717461e31b751c36a7b8c4fbc12

Observation 13340d43-2857-4c93-883c-5473ada702e0 · outbound

This paper cites PDL: A Declarative Prompt Programming Language.

Representing Prompting Patterns with PDL: Compliance Agent Case Study PDL: A Declarative Prompt Programming Language

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:54.974620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:54.974620Z digest=sha256:7caad84711f32dcd2bd6cede2364ee59605ea2a372c0b25845ea1f08441f4fae

Observation 2be797c0-2f30-4cdc-ba86-022099d2abe1 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Chain-of-thought prompting elicits reasoning in large language models

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.192423Z

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=2026-08-06T19:09:54.980408Z digest=sha256:fc687b4f961c70772595740e65290dc4138d18d72b3777e3a72be887ba96660d

Observation 501b3037-ce44-4726-939c-47efc781a8c8 · outbound

This paper cites Efficient Guided Generation for Large Language Models.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Efficient Guided Generation for Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:54.987291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:54.987291Z digest=sha256:991a7868a7900e39af0863557d3a88b62da3dfa0150450a3a5299d1464d281c4

Observation ff64b672-e2bd-4df3-b538-635470adf725 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Representing Prompting Patterns with PDL: Compliance Agent Case Study AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:54.993112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:54.993112Z digest=sha256:85032ef79415281a1433122971b469fb23e2fc00dd12e5dfc807a75f890c45bb

Observation c305f644-475d-43b4-b410-5311ba94d224 · outbound

This paper cites Decoupling reasoning from observations for efficient augmented language models, September 2023.

Representing Prompting Patterns with PDL: Compliance Agent Case Study Decoupling reasoning from observations for efficient augmented language models, September 2023

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.145682Z

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=2026-08-06T19:09:55.000274Z digest=sha256:4641c0356ea3421a2be329aa7d2dee886bc67d4b6bf833c4fcd8f229eb61c1fb

Observation 352b6747-d306-407b-a752-31bb8340876f · outbound

This paper cites R., and Cao, Y.

Representing Prompting Patterns with PDL: Compliance Agent Case Study R., and Cao, Y

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:09:55.119500Z

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=2026-08-06T19:09:55.010077Z digest=sha256:702e26b97bc820d6fe2c73f1ebab48e7160eb6be515216817f6e4a15f31de3be

Observation 5d15497b-ae09-421c-886d-17e40a87c272 · outbound

This paper cites EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms.

Representing Prompting Patterns with PDL: Compliance Agent Case Study EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:55.016338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:55.016338Z digest=sha256:cf8af108899420cec567c017a29cf42651d6347ec8c8b3596825e93fd3c69ac0

Observation 5c336b28-40f2-4ac4-971b-ba4dcbe9e320 · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

Representing Prompting Patterns with PDL: Compliance Agent Case Study SGLang: Efficient Execution of Structured Language Model Programs

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:55.024301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:09:55.024301Z digest=sha256:f9a3e277b10d5c8913d5e13abf3fd3a96ee5c48f15aca010d826cb8052b16281

Pith citing papers

No inbound Pith citation observations are available.