Paper Citation Record · LEDGER

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

As of 9 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 6 inbound Pith citation observations for arXiv:2506.05614.

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

pith.paper-citation-record.v1
2506.05614 v1

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:41.915526Z

measured 96 of 96 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-02T20:04:32.823497Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:07:21.055084Z

Reference resolution

90 of 90 outbound references displayed

verified exact7
verified fuzzy38
unresolved44
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0b26cd19-fbd7-4dc9-b118-d4d395473cf7 · outbound

This paper cites Attention is all you need,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Attention is all you need,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.499611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf224386-b520-4d4f-974a-7d0a9454f98c · outbound

This paper cites Lost in translation: A study of bugs introduced by large language models while translating code,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Lost in translation: A study of bugs introduced by large language models while translating code,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.547767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2824427-9241-4a68-bda4-61b25742ef1b · outbound

This paper cites Transagents: Build your translation company with language agents,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Transagents: Build your translation company with language agents,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.637880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc18f56-50e3-4aa5-9197-1001632578d8 · outbound

This paper cites Only diff is not enough: Generating commit messages leveraging reasoning and action of large language model,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Only diff is not enough: Generating commit messages leveraging reasoning and action of large language model,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.723344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d25be2d1-4c4c-43fc-81a2-dd423959dbd0 · outbound

This paper cites Consider What Humans Consider: Optimizing Commit Message Leveraging Contexts Considered By Human.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Consider What Humans Consider: Optimizing Commit Message Leveraging Contexts Considered By Human

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.825562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3d30ff-f2fb-412a-8dff-b0534dcfd304 · outbound

This paper cites Towards an understanding of large language models in software engineering tasks,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Towards an understanding of large language models in software engineering tasks,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.928727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f22cfb99-7f25-4e72-a298-bee29d0a09a1 · outbound

This paper cites Aligning the Objective of LLM-based Program Repair.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Aligning the Objective of LLM-based Program Repair

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.995671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87d4f04e-8323-49b8-bd18-cc36fa5238b1 · outbound

This paper cites Quantifying language models’ sensitivity to spurious features in prompt design or: How i learned to start worrying about prompt formatting,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Quantifying language models’ sensitivity to spurious features in prompt design or: How i learned to start worrying about prompt formatting,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.068609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d4867f7-3d3c-4152-9f50-59471adb788c · outbound

This paper cites The Prompt Report: A Systematic Survey of Prompt Engineering Techniques.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.134402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a502619-e6e7-4541-b9ff-48b95415d8a0 · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.208328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a639eca7-85b5-4cbe-9969-ef4a47327dee · outbound

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

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Chain-of-thought prompting elicits reasoning in large language models,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.345162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc3ccb65-92ae-486f-a0ff-dbbe6ad98a75 · outbound

This paper cites An empirical comparison of pre-trained models of source code,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks An empirical comparison of pre-trained models of source code,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.397867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b339ba04-a775-4120-8aa2-4d7de931ab03 · outbound

This paper cites Contrastive Explanations for Model Interpretability.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Contrastive Explanations for Model Interpretability

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.443269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fa9a637-b828-411a-8bae-70a68c688db1 · outbound

This paper cites Llm in a flash: Efficient large language model inference with limited memory,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Llm in a flash: Efficient large language model inference with limited memory,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.504437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99805fa1-665b-44f8-bae5-df8fe8b0784f · outbound

This paper cites Exploring the potential of chatgpt in automated code refinement: An empirical study,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Exploring the potential of chatgpt in automated code refinement: An empirical study,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.546788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1d57665-5054-49f1-b24c-81902e415864 · outbound

This paper cites Harnessing Large Language Models for Curated Code Reviews.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Harnessing Large Language Models for Curated Code Reviews

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:43.721746Z

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.

Observation d0c1cf15-b39b-4922-8969-41b0c1c327ce · outbound

This paper cites Ai that builds with you,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Ai that builds with you,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.835736Z

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.

Observation f6d84666-12d4-4094-9434-eccc82537f48 · outbound

This paper cites Jetbrains ai: Optimize your workflow. with ai built for you,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Jetbrains ai: Optimize your workflow. with ai built for you,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.760337Z

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.

Observation 633c1551-294c-47e5-9bdb-a403391e78ce · outbound

This paper cites Jtype less, code more. visual studio intellicode brings ai assistance directly into your personal development flow.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Jtype less, code more. visual studio intellicode brings ai assistance directly into your personal development flow

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.532626Z

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.

Observation 61e2c28f-516b-43fb-a432-3ed6a7610f8e · outbound

This paper cites Using ai-based coding assistants in practice: State of affairs, perceptions, and ways forward,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Using ai-based coding assistants in practice: State of affairs, perceptions, and ways forward,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.309617Z

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.

Observation 482c1d8c-b9b1-4bf3-a776-9ec857b49d31 · outbound

This paper cites Large language model fine-tuning with low-rank adaptation: A performance exploration,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Large language model fine-tuning with low-rank adaptation: A performance exploration,

Reference 21

Resolution: verified exact; doi, observed 2026-08-07T10:19:42.070898Z

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.

Observation 6f24473c-b3f0-4965-ba7a-f8f20d4451df · outbound

This paper cites Available: https://visualstudio.microsoft.com/services/ intellicode/.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Available: https://visualstudio.microsoft.com/services/ intellicode/

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.439780Z

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.

Observation e7381da7-aede-4bef-af3a-17ef3cf7dc69 · outbound

This paper cites A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:43.562493Z

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.

Observation 05fa2145-faec-44f9-8777-14da0420561c · outbound

This paper cites Prompting or fine-tuning? a comparative study of large language models for taxonomy construction,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Prompting or fine-tuning? a comparative study of large language models for taxonomy construction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.065196Z

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.

Observation 6493d240-507a-47bb-8c94-670f9b642d3e · outbound

This paper cites Language models are few-shot learners,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Language models are few-shot learners,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.176555Z

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.

Observation f52f196f-6340-463f-91d4-304ae31df532 · outbound

This paper cites Language Models in Software Development Tasks: An Experimental Analysis of Energy and Accuracy.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Language Models in Software Development Tasks: An Experimental Analysis of Energy and Accuracy

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:37.386229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22c9f2dc-dc0f-41bc-89e9-3deee0512e7d · outbound

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

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Prompting is programming: A query language for large language models,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.947151Z

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.

Observation 71f97407-2251-4fd0-998f-bd500409a3fc · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks A Survey on Large Language Models for Code Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:37.313276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05776967-e948-44f6-b0b8-66184f8e4b8c · outbound

This paper cites Interpreting Language Models with Contrastive Explanations.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Interpreting Language Models with Contrastive Explanations

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:43.158571Z

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.

Observation 239ff50b-86d7-45c4-a43f-1856535876ef · outbound

This paper cites CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:37.656335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9acfede8-c769-4376-9185-b371461c4b59 · outbound

This paper cites Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:43.347758Z

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.

Observation e27e82b9-6cb0-4ede-b2d6-0c0a221bae63 · outbound

This paper cites Learning and evaluating contextual embedding of source code,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Learning and evaluating contextual embedding of source code,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.486838Z

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.

Observation 09ab8f78-3d7e-42e9-86cd-542a3a927b01 · outbound

This paper cites Towards a big data curated benchmark of inter-project code clones,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Towards a big data curated benchmark of inter-project code clones,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.333422Z

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.

Observation e890287f-3899-45eb-98d2-ab32363d8bd6 · outbound

This paper cites voyage-code-2: Elevate your code retrieval,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks voyage-code-2: Elevate your code retrieval,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.776953Z

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.

Observation 64476724-9aab-4208-8246-1805834d24ff · outbound

This paper cites Available: https://blog.voyageai.com/2024/01/23/ voyage-code-2-elevate-your-code-retrieval/.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Available: https://blog.voyageai.com/2024/01/23/ voyage-code-2-elevate-your-code-retrieval/

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.638217Z

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.

Observation 0c3bd898-b2f1-4ccf-93c1-cf7ce73a43f6 · outbound

This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:38.279731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ae86ecb-90e9-4c15-890b-20b6b254404b · outbound

This paper cites An empirical study on learning bug-fixing patches in the wild via neural machine translation,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks An empirical study on learning bug-fixing patches in the wild via neural machine translation,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:38.404790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af590042-f354-4c7c-bcea-216a765d561b · outbound

This paper cites CoSQA: 20,000+ web queries for code search and question answering,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks CoSQA: 20,000+ web queries for code search and question answering,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:48.163682Z

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.

Observation eaba82a3-6aba-452c-8ae8-82fe4990cbb7 · outbound

This paper cites CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:38.119703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57b7b22c-366d-4c75-a13d-42f081b5a240 · outbound

This paper cites On learning meaningful assert statements for unit test cases,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks On learning meaningful assert statements for unit test cases,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:38.691809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb9339ce-5764-49df-ac2b-fc66618f8fc9 · outbound

This paper cites Mapping language to code in programmatic context,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Mapping language to code in programmatic context,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.863732Z

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.

Observation b23e680e-95c6-4851-b0f4-73068b0ab326 · outbound

This paper cites A generative and mutational approach for synthesizing bug- exposing test cases to guide compiler fuzzing,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks A generative and mutational approach for synthesizing bug- exposing test cases to guide compiler fuzzing,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.978018Z

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.

Observation 5b1c50ee-9d1a-4db1-a0a8-f858d7fbc6ea · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Bleu: a method for automatic evaluation of machine translation,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:38.604303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc0822d-c4fd-4810-977a-902a7c829b29 · outbound

This paper cites Selective Annotation Makes Language Models Better Few-Shot Learners.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Selective Annotation Makes Language Models Better Few-Shot Learners

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:39.117449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8765d6cf-6cdb-4bdb-9ce7-f1dc2ce120ac · outbound

This paper cites Exploring Demonstration Ensembling for In-context Learning.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Exploring Demonstration Ensembling for In-context Learning

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:42.801691Z

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.

Observation 59858805-2848-489f-a9c1-64f320d71519 · outbound

This paper cites Qualitative content analysis,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Qualitative content analysis,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.707217Z

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.

Observation f592f0de-d8e8-4a5a-b672-03a62dc475b2 · outbound

This paper cites What makes good in-context examples for GPT-3?.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks What makes good in-context examples for GPT-3?

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.524230Z

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.

Observation 178fe493-d978-46ec-ae32-3831ecc9d122 · outbound

This paper cites Contrastive Chain-of-Thought Prompting.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Contrastive Chain-of-Thought Prompting

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:39.628518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d12859b-1ebe-4eec-893a-b14e187f4c81 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:39.817017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07c0cfba-37a5-41bf-8b43-b162cd50ea19 · outbound

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

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks React: Synergizing reasoning and acting in language models,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:39.400333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6eea84a-0e94-4930-a5d6-8960d7312978 · outbound

This paper cites jina-embeddings-v2-base-code,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks jina-embeddings-v2-base-code,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.345047Z

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.

Observation 51d1c1a1-d07d-4ddd-8df9-8786e2231c73 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Self-refine: Iterative refinement with self-feedback,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.194302Z

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.

Observation 96e119f7-bc5b-43dd-91d9-023d68e8f65f · outbound

This paper cites Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generator.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generator

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.369919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57d246c9-e1e1-42b0-b6fd-0d2abb1cf7c2 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Measuring and Narrowing the Compositionality Gap in Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:39.930038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb168e61-61a1-4440-9d9c-9c66400ca860 · outbound

This paper cites Universal Self-Consistency for Large Language Model Generation.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Universal Self-Consistency for Large Language Model Generation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.047792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcf8c0c4-aceb-43d6-8f47-a9c193630822 · outbound

This paper cites Large Language Models Understand and Can be Enhanced by Emotional Stimuli.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.566515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a913517-8165-4b51-a7cf-2f0c70443db1 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Self-Refine: Iterative Refinement with Self-Feedback

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.327107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5166dc91-ecfa-4a99-88db-d20dbaab96d8 · outbound

This paper cites Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.677055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53c354b0-3667-4f10-8c58-6f2d395c3cc4 · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Thread of Thought Unraveling Chaotic Contexts

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.438435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e167c696-0bfd-40cc-97ec-8f869892c140 · outbound

This paper cites Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.500713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c860ddb-6a62-4fbb-be95-cfda7a2c1fe4 · outbound

This paper cites Prompt engineering: How prompt vocabulary af- fects domain knowledge,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Prompt engineering: How prompt vocabulary af- fects domain knowledge,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.831971Z

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.

Observation 63929a12-7ee9-4e9b-82d7-1c8419f63185 · outbound

This paper cites Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.637776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc498f05-2c84-4de8-91ef-a851c046cc68 · outbound

This paper cites Investigating the accuracy of chatgpt as a writing error correction tool,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Investigating the accuracy of chatgpt as a writing error correction tool,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.566118Z

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.

Observation 9d4b3d7f-30fa-41ce-91af-568d219633d1 · outbound

This paper cites RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.728914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24600b8f-3d29-4421-914d-0b6102ec6cb7 · outbound

This paper cites Large language models as analogical reasoners,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Large language models as analogical reasoners,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:47.029476Z

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.

Observation 4a7f3f69-c867-4978-991a-263c80b1904d · outbound

This paper cites Large Language Models as Analogical Reasoners.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Large Language Models as Analogical Reasoners

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:40.852014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2070ae9-58f2-4bf7-a399-b1fefdb2b30d · outbound

This paper cites Qwen2.5-Coder Technical Report.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Qwen2.5-Coder Technical Report

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:41.127364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e42f6b4-037d-424e-9196-042122801803 · outbound

This paper cites Chatgpt: Optimizing language models for dialogue,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Chatgpt: Optimizing language models for dialogue,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.698658Z

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.

Observation e4b86b61-f279-4923-b3a7-8ca2636a113b · outbound

This paper cites Openai o3-mini system card,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Openai o3-mini system card,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.037450Z

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.

Observation 3301a9c4-cd86-40b1-9105-ac4080c8bbe2 · outbound

This paper cites Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:41.056190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bb1f460-9eda-45d6-8f81-ce0ed3c77d01 · outbound

This paper cites Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.424209Z

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.

Observation 3a11c2fa-1f9b-46a6-bab9-ac9816409446 · outbound

This paper cites DeepSeek-V3 Technical Report.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks DeepSeek-V3 Technical Report

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:41.106645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8040fde9-a17d-4c07-bf82-451d1b4436b1 · outbound

This paper cites The technique of clear writing,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks The technique of clear writing,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.318588Z

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.

Observation 14f8ba76-3002-4a00-bca3-460e4c15e5df · outbound

This paper cites Llama 3.3 70b instruct model card,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Llama 3.3 70b instruct model card,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:46.254819Z

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.

Observation 92ff6731-d4ee-4537-8499-f5a3d7f1c8f4 · outbound

This paper cites Quality control in software documentation: Measurement of text comprehensibility,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Quality control in software documentation: Measurement of text comprehensibility,

Reference 75

Resolution: verified exact; raw_fallback, observed 2026-08-07T10:19:42.329890Z

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.

Observation 7e39fb8b-133d-4d5f-811e-e4de695bf3ea · outbound

This paper cites Together models,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Together models,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.843025Z

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.

Observation 67567a3d-3f59-49c1-9c96-47972a129af9 · outbound

This paper cites Cutting the gordian knot: The moving-average type–token ratio (mattr),.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Cutting the gordian knot: The moving-average type–token ratio (mattr),

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.702749Z

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.

Observation e182a3ca-b83b-4ad0-a1a9-83c162fb90e0 · outbound

This paper cites Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.484049Z

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.

Observation 654ab202-de5d-428d-ba94-1281d04d6753 · outbound

This paper cites What makes good in-context demonstrations for code intelligence tasks with llms?.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks What makes good in-context demonstrations for code intelligence tasks with llms?

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:44.891011Z

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.

Observation 9ec518ab-0427-4f14-8436-840c32336053 · outbound

This paper cites A new readability yardstick.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks A new readability yardstick

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.154212Z

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.

Observation 1639bf29-7825-4548-9739-4329f1cce986 · outbound

This paper cites Card-sorting: From text to themes,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Card-sorting: From text to themes,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:44.482841Z

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.

Observation 5fe931e9-350b-466c-8334-727f1037af44 · outbound

This paper cites The proof and measurement of association between two things,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks The proof and measurement of association between two things,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:41.446205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4569751-04ca-4770-8f46-517cee4fa26f · outbound

This paper cites Logic and causal attribution.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Logic and causal attribution

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:45.011779Z

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.

Observation a8de6399-abc5-4603-904f-40bdfb6337e9 · outbound

This paper cites Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:41.574862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 979ed27a-6530-430b-a74a-a7452e497d1f · outbound

This paper cites Advancing conversational ai: Best practices in prompt engineering for enhanced chatbot performance,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Advancing conversational ai: Best practices in prompt engineering for enhanced chatbot performance,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:44.670530Z

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.

Observation e2b4a79d-54a1-4632-a26a-9c8e9ea28204 · outbound

This paper cites an unresolved cited work.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Unresolved cited work

Reference 88

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T10:19:44.306203Z

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.

Observation 0f630f69-6c95-460b-b294-5b62e5d3b582 · outbound

This paper cites Open coding descriptions,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Open coding descriptions,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:44.105680Z

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.

Observation 1845aa95-c379-4ed7-ae77-8df106f9d662 · outbound

This paper cites GitHub - prompt-study/prompt-tasks-study — github.com,.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks GitHub - prompt-study/prompt-tasks-study — github.com,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:43.937993Z

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.

Observation 0d479eae-5909-4abb-b841-6fca4ac61206 · outbound

This paper cites Available: https://doi.org/10.1145/3560815.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Available: https://doi.org/10.1145/3560815

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:36.283740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06396820-09d7-491a-9883-36ad7324adee · outbound

This paper cites Available: https://www.jetbrains.com/ai/.

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks Available: https://www.jetbrains.com/ai/

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:49.638847Z

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.

Pith citing papers

Observation 1ded687d-bebf-4235-b14a-7ebea4c3a8b4 · inbound

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries cites this paper.

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:24.548425Z

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.

Observation 178fec85-be06-4151-8279-c54ec46075e5 · inbound

PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responses cites this paper.

PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responses Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:00:02.974189Z

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.

Observation da76e583-dfde-44c6-ac76-0e9693b1fcd4 · inbound

TDD Governance for Multi-Agent Code Generation via Prompt Engineering cites this paper.

TDD Governance for Multi-Agent Code Generation via Prompt Engineering Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:16:26.976445Z

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.

Observation 289cc4b1-515d-4a62-a442-9b2616d0e52a · inbound

Beyond Compilation: Evaluating Faithful Natural-Language-to-Lean Statement Formalization cites this paper.

Beyond Compilation: Evaluating Faithful Natural-Language-to-Lean Statement Formalization Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T13:15:45.414900Z

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.

Observation 2f08521b-7767-4010-98f4-d41d281f269e · inbound

Comparing Large Language Models on Scrum Certification-Style Questions: Accuracy, Stability, and Error Patterns cites this paper.

Comparing Large Language Models on Scrum Certification-Style Questions: Accuracy, Stability, and Error Patterns Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:07:21.025791Z

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.

Observation 94c0defb-a83d-480f-9846-20e178534476 · inbound

Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study cites this paper.

Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:07:21.056949Z

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.