Paper Citation Record · LEDGER

What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2409.08775.

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

pith.paper-citation-record.v1
2409.08775 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:44:34.392483Z

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

5
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 373e1eb8-8857-4959-806b-ea2147af7d4b · inbound

Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution cites this paper.

Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T18:01:38.632847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c55cb9b1-8948-4d1f-a267-b0aaef0e29b4 · inbound

Steering Semantic Data Processing With DocWrangler cites this paper.

Steering Semantic Data Processing With DocWrangler What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T11:44:34.392483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36c95f29-c502-440b-b495-5a0857dc77db · inbound

"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code cites this paper.

"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:07:00.798748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4ee2232-c976-4c02-9873-a47688f21a07 · inbound

Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering cites this paper.

Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:20.477208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1633fada-4a8a-404a-b5b1-d59f88851230 · inbound

Who's the Leader? Analyzing Novice Workflows in LLM-Assisted Debugging of Machine Learning Code cites this paper.

Who's the Leader? Analyzing Novice Workflows in LLM-Assisted Debugging of Machine Learning Code What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:19.494724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3269100d-8b72-4d52-9314-98151827520f · inbound

From Legal Text to Tech Specs: Generative AI's Interpretation of Consent in Privacy Law cites this paper.

From Legal Text to Tech Specs: Generative AI's Interpretation of Consent in Privacy Law What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T19:56:41.089970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83ef8830-eb2a-407b-922b-9c8f6c304d26 · inbound

Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students cites this paper.

Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T16:09:18.973771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc0795e7-6612-49e2-ba90-189b793226dc · inbound

ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User Prompts cites this paper.

ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User Prompts What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:52.659780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8a8af8b-27cc-4599-bf07-fe854a1595ee · inbound

Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI cites this paper.

Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-06-30T02:16:06.474189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f631af5d-1bfd-4d44-912b-6a0f61b19107 · inbound

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools cites this paper.

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T02:16:06.474189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.