mukhal/PromptRank
[ACL 2023] Few-shot Reranking for Multi-hop QA via Language Model Prompting
This tool helps improve the accuracy of open-domain question-answering systems, especially for complex questions that require stitching together information from multiple documents. It takes a collection of potential document paths (sequences of documents relevant to a question) and an instruction, then uses a large language model to score and re-rank these paths. The output is a more accurately ordered list of document paths, which can lead to better answers for multi-hop questions. This would be used by researchers and developers building advanced QA systems.
Use this if you need to re-rank retrieved document paths to find the most relevant information for multi-hop questions, especially in zero- or few-shot scenarios.
Not ideal if you are looking for a complete end-to-end question-answering system rather than a component for re-ranking document paths.
Stars
27
Forks
3
Language
Python
License
—
Category
Last pushed
Oct 19, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/prompt-engineering/mukhal/PromptRank"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
meta-prompting/meta-prompting
Official implementation of Meta Prompting for AI Systems (https://arxiv.org/abs/2311.11482)
auniquesun/Point-PRC
[NeurIPS 2024] Official implementation of the paper "Point-PRC: A Prompt Learning Based...
slashrebootofficial/simulated-metacognition-in-open-source-llms
This repository archives artifacts (prompts, configs, logs, and scripts) from a series of...
UKPLab/emnlp2024-code-prompting
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs. EMNLP 2024
egmaminta/GEPA-Lite
A lightweight implementation of the GEPA (Genetic-Pareto) prompt optimization method for large...