# Addressee and Response Selection for Multilingual Conversation

arXiv: https://arxiv.org/abs/1808.03915 · HTML: https://mlsanity.com/paper/1808.03915/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2018.

## Built on by (most cited first, 4 of 4)

- [MDIA: A Benchmark for Multilingual Dialogue Generation in 46 Languages](https://mlsanity.com/paper/2208.13078/) (2022)
- [xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark](https://mlsanity.com/paper/2310.08958/) (2023)
- [Multi-Party Conversational Agents: A Survey](https://mlsanity.com/paper/2505.18845/) (2025)
- [On the Structure of Address in Multi-Party Dialogue: From Discrete Labels to Continuous Levels](https://mlsanity.com/paper/2607.15648/) (2026)

## Abstract (arXiv)

Developing conversational systems that can converse in many languages is an interesting challenge for natural language processing. In this paper, we introduce multilingual addressee and response selection. In this task, a conversational system predicts an appropriate addressee and response for an input message in multiple languages. A key to developing such multilingual responding systems is how to utilize high-resource language data to compensate for low-resource language data. We present several knowledge transfer methods for conversational systems. To evaluate our methods, we create a new multilingual conversation dataset. Experiments on the dataset demonstrate the effectiveness of our methods.