question-answering

This repository uses pretrain BERT embeddings for transfer learning in QA domain

DrFAQ is a plug-and-play question answering NLP chatbot that can be generally applied to any organisation's text corpora.

An alternative EQA paradigm and informative benchmark + models (BMVC 2019, ViGIL 2019 spotlight)

Windows + Docker + Python 基于 Milvus + MySQL + Redis + 大模型的私有化 RAG 问答系统

Question Answering model based on DistilBERT, trained and evaluated on the SQUAD dataset

indoBERT Base-Uncased fine-tuned on Translated Squad v2.0

Code and dataset release for "PACS: A Dataset for Physical Audiovisual CommonSense Reasoning" (ECCV 2022)

Fine tuned llama 3 models for context based question answering in bengali language.

A Question Generation Application leveraging RAG and Weaviate vector store to be able to retrieve relative contexts and generate a more useful answer-aware questions

LLM-powered financial analyst using LoRA-tuned Llama-3 and RAG pipeline to answer complex queries over SEC 10-K filings with contextual accuracy.

The official implementation of NeurlPS 2025 D&B paper: IndustryEQA: Pushing the frontiers of Embodied Question Answering in Industrial Scenarios.

Production-ready Retrieval Augmented Generation (RAG) system with hybrid retrieval, advanced evaluation metrics, and monitoring. Build enterprise LLM applications with reduced hallucinations, better context management, and comprehensive observability.

JGLUE: Japanese General Language Understanding Evaluation for huggingface datasets

预训练模型知识量度量竞赛 Baseline F1 0.35 BERTForMaskedLM

Multimodal Document Processing RAG with LangChain

Development and deployment on AWS of a question-answer LLM model using Llama2 with 7B parameters and RAG with LangChain

Transformers PHP is a toolkit for PHP developers to add machine learning magic to their projects easily.

This repository contains a system for generating question-answer pairs for FINE-TUNING LLMs from the data you have.

This repo contains evaluation code for MM-IQ benchmark.

⚕️ Multi-agent SLM system for medical question answering — domain-aware, private-by-design, cloud-free