18 citations · 23 across the 15 of their papers we have counts for
6 papers · 1 filter
NiuTrans.LMT: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs
Yingfeng Luo, Ziqiang Xu, Yuxuan Ouyang +9
Large language models have significantly advanced Multilingual Machine Translation (MMT), yet scaling to many languages while keeping quality robust across directions remains chall…
Scale-Aware Curriculum Learning for Ddata-Efficient Lung Nodule Detection with YOLOv11
Yi Luo, Yike Guo, Hamed Hooshangnejad +1
Lung nodule detection in chest CT is crucial for early lung cancer diagnosis, yet existing deep learning approaches face challenges when deployed in clinical settings with limited…
Step-level Verifier-guided Hybrid Test-Time Scaling for Large Language Models
Kaiyan Chang, Yonghao Shi, Chenglong Wang +7
Test-Time Scaling (TTS) is a promising approach to progressively elicit the model's intelligence during inference. Recently, training-based TTS methods, such as continued reinforce…
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine Translation
Yingfeng Luo, Tong Zheng, Yongyu Mu +8
The field of neural machine translation (NMT) has changed with the advent of large language models (LLMs). Much of the recent emphasis in natural language processing (NLP) has been…
Enhancing Speech Large Language Models with Prompt-Aware Mixture of Audio Encoders
Weiqiao Shan, Yuang Li, Yuhao Zhang +9
Connecting audio encoders with large language models (LLMs) allows the LLM to perform various audio understanding tasks, such as automatic speech recognition (ASR) and audio captio…
Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal Models
Yongyu Mu, Hengyu Li, Junxin Wang +7
Previous work on augmenting large multimodal models (LMMs) for text-to-image (T2I) generation has focused on enriching the input space of in-context learning (ICL). This includes p…