CindyTing

adversarial-nibbler

This dataset contains results from all rounds of Adversarial Nibbler. This data includes adversarial prompts fed into public generative text2image models and validations for unsafe images. There will be two sets of data: all prompts submitted and all prompts attempted (sent to t2i models but not submitted as unsafe).

kNN-CM

resta

Restore safety in fine-tuned language models through task arithmetic

mean-opinion-score

Python library for calculating the mean opinion score and 95% confidence interval of the standard deviation of text-to-speech ratings according to Ribeiro et al. (2011).

red-instruct

Codes and datasets of the paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment

identifiable-transformers

VIP

Our EMNLP 2022 paper on VIP-Based Prompting for Parameter-Efficient Learning

instruct-eval

This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.

Great-Deep-Learning-Tutorials

A Great Collection of Deep Learning Tutorials and Repositories

IEMOCAP_EMOTION_Recognition

Emotion recognition from IEMOCAP datasets.

Prompt-Tuning

Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"

MIPS

attentions

PyTorch implementation of some attentions for Deep Learning Researchers.

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

erc

Emotion recognition in conversation

cfvqa

[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

Question-Answering

Question Answering over Knowledge Bases

IRNQA

Pytorch implementation of "An Interpretable Reasoning Network for Multi-Relation Question Answering"

IRN

code and data for my COLING paper "An Interpretable Reasoning Network for Multi-Relation Question Answering"

UHop

UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering

ABigSurvey

A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).

relation-gcn-pytorch

pytorch implementaion of Relational Graph Convolutional Networks

EmbedKGQA

ACL 2020: Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings

Causal_Reading_Group

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

relational-gcn

Keras-based implementation of Relational Graph Convolutional Networks

QA-Survey-CN

北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答（KBQA），基于文本的问答系统（TextQA），基于表格的问答系统（TableQA）、基于视觉的问答系统（VisualQA）和机器阅读理解（MRC）等，每类任务分别对学术界和工业界进行了相关总结。

awesome-causal-inference

A (concise) curated list of awesome Causal Inference resources.

Fast-TransX

An Efficient implementation of TransE and its extended models for Knowledge Representation Learning

CS224n-winter-together

an Open Course Platform for Stanford CS224n (2020 Winter)

Awesome-Interview

Collection of awesome interview references.