CausaLM: Causal Model Explanation Through Counterfactual Language Models

Overview

CausaLM: Causal Model Explanation Through Counterfactual Language Models

Authors:

Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart

Abstract:

Understanding predictions made by deep neural networks is notoriously difficult, but also crucial to their dissemination. As all ML-based methods, they are as good as their training data, and can also capture unwanted biases. While there are tools that can help understand whether such biases exist, they do not distinguish between correlation and causation, and might be ill-suited for text-based models and for reasoning about high level language concepts. A key problem of estimating the causal effect of a concept of interest on a given model is that this estimation requires the generation of counterfactual examples, which is challenging with existing generation technology. To bridge that gap, we propose CausaLM, a framework for producing causal model explanations using counterfactual language representation models. Our approach is based on fine-tuning of deep contextualized embedding models with auxiliary adversarial tasks derived from the causal graph of the problem. Concretely, we show that by carefully choosing auxiliary adversarial pre-training tasks, language representation models such as BERT can effectively learn a counterfactual representation for a given concept of interest, and be used to estimate its true causal effect on model performance. A byproduct of our method is a representation that is unaffected by the tested concept, which can be useful in mitigating unwanted bias ingrained in the data.

Links:

Paper

Code

Data

Owner
Amir Feder
PhD student at the Technion, researching Natural Language Processing and Causal Inference.
Amir Feder
Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

29 Aug 23, 2022
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion This repo intends to release code for our work: Zhaoyang Lyu*, Zhifeng

Zhaoyang Lyu 68 Jan 03, 2023
Python scripts for performing stereo depth estimation using the HITNET Tensorflow model.

HITNET-Stereo-Depth-estimation Python scripts for performing stereo depth estimation using the HITNET Tensorflow model from Google Research. Stereo de

Ibai Gorordo 76 Jan 02, 2023
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3

4 Apr 14, 2022
Extracts data from the database for a graph-node and stores it in parquet files

subgraph-extractor Extracts data from the database for a graph-node and stores it in parquet files Installation For developing, it's recommended to us

Cardstack 0 Jan 10, 2022
Styled Augmented Translation

SAT Style Augmented Translation Introduction By collecting high-quality data, we were able to train a model that outperforms Google Translate on 6 dif

139 Dec 29, 2022
Thermal Control of Laser Powder Bed Fusion using Deep Reinforcement Learning

This repository is the implementation of the paper "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", linked here. The project makes use of the Deep Reinforcement Library

BaratiLab 11 Dec 27, 2022
A Python library for common tasks on 3D point clouds

Point Cloud Utils (pcu) - A Python library for common tasks on 3D point clouds Point Cloud Utils (pcu) is a utility library providing the following fu

Francis Williams 622 Dec 27, 2022
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

Microsoft 14.5k Jan 08, 2023
Official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

1 SNAS4MTF This repo is the official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting. 1.1 The frame

SZJ 5 Sep 21, 2022
NumQMBasic - A mini-course offered to Undergrad physics students

The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th

Raghu 35 Dec 05, 2022
Implementation for Simple Spectral Graph Convolution in ICLR 2021

Simple Spectral Graph Convolutional Overview This repo contains an example implementation of the Simple Spectral Graph Convolutional (S^2GC) model. Th

allenhaozhu 64 Dec 31, 2022
Python code for loading the Aschaffenburg Pose Dataset.

Aschaffenburg Pose Dataset (APD) This repository contains Python code for loading and filtering the Aschaffenburg Pose Dataset. The dataset itself and

1 Nov 26, 2021
SuperSDR: multiplatform KiwiSDR + CAT transceiver integrator

SuperSDR SuperSDR integrates a realtime spectrum waterfall and audio receive from any KiwiSDR around the world, together with a local (or remote) cont

Marco Cogoni 30 Nov 29, 2022
ONNX-PackNet-SfM: Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX

Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX

Ibai Gorordo 14 Dec 09, 2022
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc

Matt Cooper 704 Nov 26, 2022
GAN encoders in PyTorch that could match PGGAN, StyleGAN v1/v2, and BigGAN. Code also integrates the implementation of these GANs.

MTV-TSA: Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions. This is the official code release fo

owl 37 Dec 24, 2022
ACV is a python library that provides explanations for any machine learning model or data.

ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based mod

Salim Amoukou 85 Dec 27, 2022
This library is a location of the LegacyLogger for PyTorch Lightning.

neptune-contrib Documentation See neptune-contrib documentation site Installation Get prerequisites python versions 3.5.6/3.6 are supported Install li

neptune.ai 26 Oct 07, 2021
This project aims to be a handler for input creation and running of multiple RICEWQ simulations.

What is autoRICEWQ? This project aims to be a handler for input creation and running of multiple RICEWQ simulations. What is RICEWQ? From the descript

Yass Fuentes 1 Feb 01, 2022