1 citations · 2 across the 10 of their papers we have counts for
10 papers
MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference
Bo Li, Chuan Wu, Shaolin Zhu
Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant efficiency bottleneck during Expert Parallelism (EP) inference due to the straggler effect…
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence
Xiang An, Yin Xie, Feilong Tang +27
We introduce LLaVA-OneVision-2 (LLaVA-OV-2), the most capable vision-language model in the LLaVA-OneVision series to date, achieving superior performance across a broad range of mu…
Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs
Bo Li, Tianyu Dong, Shaolin Zhu +1
Large Language Models (LLMs) have shown great promise in multilingual machine translation (MT), even with limited bilingual supervision. However, fine-tuning LLMs with parallel cor…
VaaWIT: Visual-Aware Adaptation of Large Language Models for Multilingual Web Image Translation
Bo Li, Ronghao Chen, Ningyuan Deng +3
Translating text embedded in Web images is crucial for improving content accessibility and cross-lingual information retrieval, particularly within social media and e-commerce doma…
DisastRAG: A Multi-Source Disaster Information Integration and Access System Based on Retrieval-Augmented Large Language Models
Bo Li, Zhitong Chen, Kai Yin +3
Effective disaster management requires rapid access to information distributed across structured operational records, unstructured institutional documents, and dynamic external sou…
Denoise and Align: Diffusion-Driven Foreground Knowledge Prompting for Open-Vocabulary Temporal Action Detection
Sa Zhu, Wanqian Zhang, Lin Wang +3
Open-Vocabulary Temporal Action Detection (OV-TAD) aims to localize and classify action segments of unseen categories in untrimmed videos, where effective alignment between action…
MNAFT: modality neuron-aware fine-tuning of multimodal large language models for image translation
Bo Li, Ningyuan Deng, Tianyu Dong +3
Multimodal large language models (MLLMs) have shown impressive capabilities, yet they often struggle to effectively capture the fine-grained textual information within images cruci…
FuxiMT: Sparsifying Large Language Models for Chinese-Centric Multilingual Machine Translation
Shaolin Zhu, Tianyu Dong, Bo Li +1
In this paper, we present FuxiMT, a novel Chinese-centric multilingual machine translation model powered by a sparsified large language model (LLM). We adopt a two-stage strategy t…
MIT-10M: A Large Scale Parallel Corpus of Multilingual Image Translation
Bo Li, Shaolin Zhu, Lijie Wen
Image Translation (IT) holds immense potential across diverse domains, enabling the translation of textual content within images into various languages. However, existing datasets…
LANDeRMT: Detecting and Routing Language-Aware Neurons for Selectively Finetuning LLMs to Machine Translation
Shaolin Zhu, Leiyu Pan, Bo Li +1
Recent advancements in large language models (LLMs) have shown promising results in multilingual translation even with limited bilingual supervision. The major challenges are catas…