hyperconnect/sem-ent

An official codebase for the paper, "Measuring and Improving Semantic Diversity of Dialogue Generation", EMNLP 2022 Findings

Measuring and Improving Semantic Diversity of Dialogue Generation (ENMLP 2022 Findings)

Paper link

• https://arxiv.org/abs/2210.05725

Overview

• codes/evalutate_diversify.py - Measuring semantic diversity of dialogue generation.
• codes/train_dress.py, train_diversify_base.py - Training the model to improve the semantic diversity of dialogue generation.
• codes/dm_generator.py - A generator agent for DRESS.

Installation

• First, this code is implemented based on ParlAI and Huggingface Transformers. You need to install ParlAI and Huggingface Transformers as described in the README on those links.

• After installing ParlAI on your local, then move the codes as follows:

  • codes/evalutate_diversify.py -> parlai/scripts/evalutate_diversify.py
  • codes/train_dress.py -> parlai/scripts/train_dress.py
  • codes/train_diversify_base.py -> parlai/scripts/train_diversify_base.py
  • codes/dm_generator.py -> parlai/agents/transformer/dm_generator.py
  • codes/utils/ -> parlai/utils

• Install mauve package in ./mauve:

  pip install -e mauve

Training & Evaluation

Training

# Blender 90M
bash scripts/train_balancing.sh [init_model] 32 7e-6 dailydialog

# Bart-large
bash scripts/train_balancing_bart.sh [init_model] 16 7e-6 dailydialog

Evaluation

bash scripts/eval_dailydialog.sh [model_filename] [report_filename] 32

Citation

Please cite the following if you make use of this codebase.

@article{han2022measuring,
  title={Measuring and Improving Semantic Diversity of Dialogue Generation},
  author={Han, Seungju and Kim, Beomsu and Chang, Buru},
  journal={arXiv preprint arXiv:2210.05725},
  year={2022}
}