90 Open source projects that are alternatives of or similar to Zero-shot-Fact-Verification

Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(ICCV, 2021) paper

Zero-shot image tagging by hierarchical semantic embedding

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

No description or website provided.

[ECCV 2018] code for Choose Your Neuron: Incorporating Domain Knowledge Through Neuron Importance

Codes for the ICCV'21 paper "FREE: Feature Refinement for Generalized Zero-Shot Learning"

General-Purpose Neural Networks for Sentence Boundary Detection

Multi-hop Question Generation with Graph Convolutional Network

Text2Text: Cross-lingual natural language processing and generation toolkit

[TPAMI Special Issue on ICCV 2021 Best Papers, Oral] Just Ask: Learning to Answer Questions from Millions of Narrated Videos

Code & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"

This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

[CVPR '21] Official repository for Few-shot Image Generation via Cross-domain Correspondence

FewCLUE 小样本学习测评基准，中文版

The source code of "Language Models are Few-shot Multilingual Learners" (MRL @ EMNLP 2021)

Hands-On Deep Learning Algorithms with Python, By Packt

An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.

OpenMMLab FewShot Learning Toolbox and Benchmark

[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

[CVPR 2020 VL3] The repository for meta fine-tuning in cross-domain few-shot learning.

A novel method for few shot learning

Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

Finetuning any DNN for better embedding on neural search tasks

Official repository of https://arxiv.org/abs/2111.04040v1

Learning low-shot object classification with explicit shape bias learned from point clouds

(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks

PyTorch implementation of the paper: Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding. Su Zhu, Ruisheng Cao, Lu Chen and Kai Yu.

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection