Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Language Models are Multilingual Chain-of-Thought Reasoners

Domain:

natural language processing

Record type:

paperdataset
Creator:
ShiSuzFreWan
Host:avatar
We evaluate the reasoning abilities of large language models in multilingual settings. We introduce the Multilingual Grade School Math (MGSM) benchmark, by manually translating 250 grade-school math problems from the GSM8K dataset (Cobbe et al., 2021) into ten typologically diverse languages. We find that the ability to solve MGSM problems via chain-of-thought prompting emerges with increasing model scale, and that models have strikingly strong multilingual reasoning abilities, even in underrepresented languages such as Bengali and Swahili. Finally, we show that the multilingual reasoning abilities of language models extend to other tasks such as commonsense reasoning and word-in-context semantic judgment. The MGSM benchmark is publicly available at github.com.

Visit

arxiv.org

Languages

Swahili

Tags

Computation and LanguageArtificial IntelligenceMachine Learning

Similar

Large Reasoning Models Are (Not Yet) Multilingual Latent ReasonersSoT: Structured-of-Thought Prompting Guides Multilingual Reasoning in Large Language ModelsTIBSTC-CoT: A Multi-Domain Instruction Dataset for Chain-of-Thought Reasoning in Language ModelsHow Linguistically Fair Are Multilingual Pre-Trained Language Models?AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-ThoughtAre Knowledge and Reference in Multilingual Language Models Cross-Lingually Consistent?

Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

Large reasoning models (LRMs) achieve strong performance on mathematical reasoning tasks, often attr

SoT: Structured-of-Thought Prompting Guides Multilingual Reasoning in Large Language Models

Recent developments have enabled Large Language Models (LLMs) to engage in complex reasoning tasks t

TIBSTC-CoT: A Multi-Domain Instruction Dataset for Chain-of-Thought Reasoning in Language Models

To address the severe data scarcity in Tibetan, a low-resource language spoken by over six million p

How Linguistically Fair Are Multilingual Pre-Trained Language Models?

Massively multilingual pre-trained language models, such as mBERT and XLM-RoBERTa, have received sig

AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought

Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on

Are Knowledge and Reference in Multilingual Language Models Cross-Lingually Consistent?

Cross-lingual consistency should be considered to assess cross-lingual transferability, maintain the