most citedAdvancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models

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cs.CL20251 cited

Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study

Menglong Cui, Pengzhi Gao, Wei Liu +2

Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…

cs.CL2025

SSMLoRA: Enhancing Low-Rank Adaptation with State Space Model

Jiayang Yu, Yihang Zhang, Bin Wang +3

Fine-tuning is a key approach for adapting language models to specific downstream tasks, but updating all model parameters becomes impractical as model sizes increase. Parameter-Ef…

cs.CL2025

MERaLiON-TextLLM: Cross-Lingual Understanding of Large Language Models in Chinese, Indonesian, Malay, and Singlish

Xin Huang, Tarun Kumar Vangani, Minh Duc Pham +4

Multilingual large language models (MLLMs) have shown impressive capabilities across a variety of languages. However, efficacy can differ greatly between different language familie…

cs.CL2025

MERaLiON-AudioLLM: Bridging Audio and Language with Large Language Models

Yingxu He, Zhuohan Liu, Shuo Sun +5

We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning in One Network), the first speech-text model tailored for Singapore's multilingual and multicultural la…

cs.CL20252 cited

Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models

Bin Wang, Xunlong Zou, Shuo Sun +6

Singlish, a Creole language rooted in English, is a key focus in linguistic research within multilingual and multicultural contexts. However, its spoken form remains underexplored,…