97 citations · 129 across the 21 of their papers we have counts for
21 papers
Soft Alignment of Modality Space for End-to-end Speech Translation
Yuhao Zhang, Kaiqi Kou, Bei Li +4
End-to-end Speech Translation (ST) aims to convert speech into target text within a unified model. The inherent differences between speech and text modalities often impede effectiv…
Rethinking and Improving Multi-task Learning for End-to-end Speech Translation
Yuhao Zhang, Chen Xu, Bei Li +4
Significant improvements in end-to-end speech translation (ST) have been achieved through the application of multi-task learning. However, the extent to which auxiliary tasks are h…
Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs
Yuxin Zuo, Bei Li, Chuanhao Lv +3
This paper presents an in-depth study of multimodal machine translation (MMT), examining the prevailing understanding that MMT systems exhibit decreased sensitivity to visual infor…
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation
Chenglong Wang, Hang Zhou, Yimin Hu +5
Applying Reinforcement Learning (RL) to sequence generation models enables the direct optimization of long-term rewards (\textit{e.g.,} BLEU and human feedback), but typically requ…
ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning
Xiao Xu, Bei Li, Chenfei Wu +6
Two-Tower Vision-Language (VL) models have shown promising improvements on various downstream VL tasks. Although the most advanced work improves performance by building bridges bet…
Deliberate then Generate: Enhanced Prompting Framework for Text Generation
Bei Li, Rui Wang, Junliang Guo +7
Large language models (LLMs) have shown remarkable success across a wide range of natural language generation tasks, where proper prompt designs make great impacts. While existing…