Revisiting Prompt Engineering via Declarative Crowdsourcing

Summary: Treats LLMs as crowd workers and introduces declarative prompt engineering: applying declarative crowdsourcing concepts—multiple prompting strategies, consistency checks, and hybrid LLM/non‑LLM pipelines—to make prompt design systematic and cost-aware. Validated on sorting, entity resolution, and imputation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: hac4276dbc613834f
Venue: CIDR
Year: 2024
Pagerank: 7.092445e-05
Overall Rank: 3,695 | 75.16%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Aditya G. Parameswaran (University of California Berkeley)
2. Shreya Shankar (University of California Berkeley)
3. Parth Asawa (University of California Berkeley)
4. Naman Jain (University of California Berkeley)
5. Yujie Wang (University of California Berkeley)

BibTeX Citation

@inproceedings{parameswaran_cidr24,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '24},
        title = {{Revisiting Prompt Engineering via Declarative Crowdsourcing}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Parameswaran, Aditya G. and Shankar, Shreya and Asawa, Parth and Jain, Naman and Wang, Yujie},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
683	DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing	2025	VLDB	0.00014817539
748	Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing	2025	CIDR	0.00014281926
4,675	spade: Synthesizing Data Quality Assertions for Large Language Model Pipelines	2024	VLDB	6.474947e-05
4,787	Hybrid Querying Over Relational Databases and Large Language Models	2025	CIDR	6.4143303e-05
6,220	GenEdit: Compounding Operators and Continuous Improvement to Tackle Text-to-SQL in the Enterprise	2025	CIDR	5.8469622e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
92	CrowdDB: Answering Queries with Crowdsourcing	2011	SIGMOD	0.00034672523
198	CrowdER: Crowdsourcing Entity Resolution	2012	VLDB	0.00025555196
244	Evaluation of entity resolution approaches on real-world match problems	2010	VLDB	0.00023314591
257	Crowdsourced Databases: Query Processing with People	2011	CIDR	0.00022962347
266	Human-powered Sorts and Joins	2012	VLDB	0.00022739124
329	Can Foundation Models Wrangle Your Data?	2023	VLDB	0.00020858443
749	So Who Won? Dynamic Max Discovery with the Crowd	2012	SIGMOD	0.00014265279
871	Leveraging Transitive Relations for Crowdsourced Joins	2013	SIGMOD	0.00013343705
987	CrowdScreen: Algorithms for Filtering Data with Humans	2012	SIGMOD	0.00012660627
1,926	Counting with the Crowd	2013	VLDB	9.3637786e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	11,061	LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning	2026	VLDB
2	10,869	DeepPrep: An LLM-Powered Agentic System for Autonomous Data Preparation	2026	VLDB
3	11,004	LLM-CER: An Interactive System for In-context Clustering-based Entity Resolution with Large Language Models	2026	VLDB
4	5,149	LLM for Data Management	2024	VLDB
5	8,997	Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees	2026	SIGMOD
6	10,527	In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration	2026	SIGMOD
7	10,353	Making Prompts First-Class Citizens for Adaptive LLM Pipelines	2026	CIDR
8	9,069	Unveiling Challenges for LLMs in Enterprise Data Engineering	2026	VLDB
9	13,633	Prompt Editor: A Taxonomy-driven System for Guided LLM Prompt Development in Enterprise Settings	2025	SIGMOD
10	8,888	Optimized Batch Prompting for Cost-effective LLMs	2025	VLDB