Reducing Spurious Correlations for Answer Selection by Feature Decorrelation and Language Debiasing

This repository contains the code and data for the implementation of our paper.

Script

To be consistent with previous work TANDA, we base our implementation on the transformers package and use the following script to enable scan option for the package.

git clone https://github.com/huggingface/transformers.git
cd transformers
git checkout f3386 -b scan
git apply scan.diff

Then we can train the model by the script: train.sh.

Data

We initailize our pre-trained language model with checkpoints from TANDA. Specifically, we use 'RoBERTa-Base ASNQ'

Datasets

WikiQA

Download from here and questions without correct answers are removed.

SelQA

Download from here

ANTIQUE

Download from here

All datasets are processed according to the description of our paper.

Note: some hyper-parameters(such as lrbl, epochb, lambdap) may vary among different environments/software/hardware/random seeds, so careful tunning is needed.