---
license: apache-2.0
---

# FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue

We present our dialogue-pertaining model, FutureTOD, which distills future knowledge into the representation of the previous dialogue context using a self-training framework. Extensive experiments on diverse downstream dialogue tasks demonstrate the effectiveness of our model, especially its generalization, robustness, and ability to learn discriminative dialogue representations.

[This paper](https://arxiv.org/abs/2306.10315) has been accepted at the ACL 2023 Main Conference.

## Usage

We release our futuretod-base-v1.0 model here. You can use this model for downstream TOD tasks follow instructions in [FutureTOD](https://github.com/Zeng-WH/FutureTOD).

## Quotation

If you find our work helpful, please consider quoting the following papers.

```
@article{zeng2023futuretod,
  title={FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue},
  author={Zeng, Weihao and He, Keqing and Wang, Yejie and Zeng, Chen and Wang, Jingang and Xian, Yunsen and Xu, Weiran},
  journal={arXiv preprint arXiv:2306.10315},
  year={2023}
}
```