Open-source ecosystem for building AI-powered conversational solutions using RAG, agents, FSMs, and LLMs.
-
Updated
Sep 23, 2025 - Python
Open-source ecosystem for building AI-powered conversational solutions using RAG, agents, FSMs, and LLMs.
The Tensorflow implementation of "Review-driven Answer Generation for Product-related Questions in E-commerce ", WSDM 2019.
Vietnamese Legal Question Answering with Machine Reading Comprehension (MRC) and Answer Generation (AG) approches. (KSE 2024)
Work on answering questions in digital humanities (history) using various large language models (LLMs)
Code for Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning, EMNLP 2021
ViAG: A Novel Framework for Fine-tuning Answer Generation models ultilizing Encoder-Decoder and Decoder-only Transformers's architecture
Comprehensive Evaluation On Answer Calibration For Multi-Step Reasoning
In this we generate QA pairs from the paragraph content and pdf content
A Python library for generating high-quality question-answer pairs from PDF, DOCX, MD, and TXT files
This app allows users to auto-generate unlimited exam preparation questions, based off their own, or a community created question.
Open-Domain Chitchat System with Multi-Module Architecture for Enhanced Conversational AI
A Python library for generating high-quality question-answer pairs from PDF, DOCX, MD, and TXT files
Add a description, image, and links to the answer-generation topic page so that developers can more easily learn about it.
To associate your repository with the answer-generation topic, visit your repo's landing page and select "manage topics."