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Hallucinations in Large Multilingual Translation Models

This repository contains code and data for the "Hallucinations in Large Multilingual Translation Models" paper.

Data with Translations for all setups

You can dowload the translations from all models for all the natural hallucinations setups in the paper by running:

wget https://web.tecnico.ulisboa.pt/~ist178550/lmt_natural_hallucinations.zip

Generation and Detection of Natural Hallucinations

We will guide through generation with all M2M models and scoring with ALTI+. For more information, please refer to fairseq documentation and the stopes documentation.

Installation

First, start by installing the following dependencies:

python3 -m venv ltm_env
source ltm_env/bin/activate

Then install fairseq and additional dependencies:

git clone https://github.com/deep-spin/fairseq-m2m100
cd fairseq-m2m100
git fetch
git checkout alti
pip install -e .
pip install "omegaconf==2.1.2" "hydra-core==1.0.0" "antlr4-python3-runtime==4.8" "sentencepiece==0.1.97" "numpy<=1.23" "pandas<1.5" "fairscale" "einops"

After this, download the following files with the sentencepiece models, language dictionaries, etc.:

wget https://dl.fbaipublicfiles.com/m2m_100/spm.128k.model
wget https://dl.fbaipublicfiles.com/m2m_100/data_dict.128k.txt
wget https://dl.fbaipublicfiles.com/m2m_100/model_dict.128k.txt
wget https://dl.fbaipublicfiles.com/m2m_100/language_pairs.txt
wget https://dl.fbaipublicfiles.com/m2m_100/language_pairs_small_models.txt 

Now, download the models:

mkdir -p fairseq-m2m100/checkpoints/M2M/
cd fairseq-m2m100/checkpoints/M2M/
wget https://dl.fbaipublicfiles.com/m2m_100/12b_last_chk_2_gpus.pt
# rename the model to 12B_last_checkpoint.pt
wget https://dl.fbaipublicfiles.com/m2m_100/418M_last_checkpoint.pt 
wget https://dl.fbaipublicfiles.com/m2m_100/1.2B_last_checkpoint.pt 

Download the small-100 model via the Google drive link available in the official small100 repo: https://drive.google.com/file/d/1d6Nl3Pbx7hPUbNkIq-c7KBuC3Vi5rR8D/view?usp=sharing. Unzip it and copy it to the checkpoint folder folder "fairseq-m2m100/checkpoints/M2M/" or another folder of your choice. Rename the model ckpt as "small100_last_checkpoint.pt".

Generating Translations

Start by downloading all the data:

bash download_data.sh

🚨 For all the scripts below, make sure to:

• change the main_path on the first line of these scripts to your local llm-hallucination repo path.
• change the checkpoint_path if necessary.

English-Centric scenario

We will be running the English-centric scenario for 64 directions (see all directions in the main paper).

To generate the translations, you simply need to run the script:

$LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/english_centric/flores/generate_non_english_centric_translations.sh

Non English-Centric scenario

We will be running the non-English-centric scenario for 25 directions (see all directions in the main paper).

To generate the translations, you simply need to run the script:

$LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/non_english_centric/generate_non_english_centric_translations.sh

The dataframes with the translations will be saved in $FAIRSEQ_PATH/data-bin/m2m_non_english_centric/$lang_pair/dataframes.

Specialized Domain Setup

We will be running the specialized domain setup with TICO for 18 directions (see all directions in the main paper).

Just run the following script:

bash $LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/specialized_domain/generate_translations.sh

Detection with ALTI+

Install our stopes fork:

cd $LTM_HALLUCINATIONS_PATH
git clone https://github.com/deep-spin/stopes.git
cd stopes
git fetch
git checkout M2M_stopes
pip install -e .

Once that is concluded, you can obtain ALTI+ scores by running the following code:

English-Centric Setup

bash $LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/english-centric/score_with_alti.sh

Non-English-Centric Setup

bash $LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/non_english_centric/score_with_alti.sh

Specialized Domain Setup

bash $LTM_HALLUCINATIONS_PATH/hallucinations/hallucinations_natural/specialized_domain/score_with_alti.sh

If you found our work/code useful, please cite our work:

@misc{guerreiro2023hallucinations,
      title={Hallucinations in Large Multilingual Translation Models}, 
      author={Nuno M. Guerreiro and Duarte Alves and Jonas Waldendorf and Barry Haddow and Alexandra Birch and Pierre Colombo and André F. T. Martins},
      year={2023},
      eprint={2303.16104},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}