rahmanidashti/ACQSurvey
[Official] A Survey on Asking Clarification Questions Datasets in Conversational Systems - ACL 2023
This project provides a comprehensive analysis of publicly available datasets for training conversational AI systems that can ask clarifying questions. It helps developers, researchers, and product managers working on AI assistants and chatbots understand the strengths and weaknesses of different datasets, and compare evaluation metrics and benchmarks. The output includes detailed comparisons and insights into datasets for tasks like conversational search and question answering, guiding the selection of appropriate data for building more effective conversational AI.
No commits in the last 6 months.
Use this if you are building or evaluating conversational AI systems and need to understand the landscape of existing datasets for teaching your AI to ask clarifying questions.
Not ideal if you are a general user looking for a ready-to-use chatbot or an application that directly solves an end-user problem.
Stars
16
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Jun 07, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rahmanidashti/ACQSurvey"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Pinafore/qb
QANTA Quiz Bowl AI
KristiyanVachev/Question-Generation
Generating multiple choice questions from text using Machine Learning.
wuba/qa_match
A simple effective ToolKit for short text matching
PolyAI-LDN/conversational-datasets
Large datasets for conversational AI
mcQA-suite/mcQA
🔮 Answering multiple choice questions with Language Models.