Papers
arxiv:2401.10695

LangBridge: Multilingual Reasoning Without Multilingual Supervision

Published on Jan 19
Authors:
,
,

Abstract

We introduce LangBridge, a zero-shot approach to adapt language models for multilingual reasoning tasks without multilingual supervision. LangBridge operates by bridging two models, each specialized in different aspects: (1) one specialized in understanding multiple languages (e.g., mT5 encoder) and (2) one specialized in reasoning (e.g., Orca 2). LangBridge connects the two models by introducing minimal trainable parameters between them. Despite utilizing only English data for training, LangBridge considerably enhances the performance of language models on low-resource languages across mathematical reasoning, coding, and logical reasoning. Our analysis suggests that the efficacy of LangBridge stems from the language-agnostic characteristics of multilingual representations. We publicly release our code and models.

Community

Sign up or log in to comment

Models citing this paper 12

Browse 12 models citing this paper

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2401.10695 in a dataset README.md to link it from this page.

Spaces citing this paper 1

Collections including this paper 4