2 citations · 3 across the 12 of their papers we have counts for
4 papers · 1 filter
Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance
Shaomu Tan, Christof Monz
Multilingual Neural Machine Translation (MNMT) facilitates knowledge sharing but often suffers from poor zero-shot (ZS) translation qualities. While prior work has explored the cau…
UvA-MT's Participation in the WMT23 General Translation Shared Task
Di Wu, Shaomu Tan, David Stap +2
This paper describes the UvA-MT's submission to the WMT 2023 shared task on general machine translation. We participate in the constrained track in two directions: English <-> Hebr…
Document AI: A Comparative Study of Transformer-Based, Graph-Based Models, and Convolutional Neural Networks For Document Layout Analysis
Sotirios Kastanas, Shaomu Tan, Yi He
Document AI aims to automatically analyze documents by leveraging natural language processing and computer vision techniques. One of the major tasks of Document AI is document layo…
Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
Baohao Liao, Shaomu Tan, Christof Monz
Parameter-efficient fine-tuning (PEFT) of pre-trained language models (PLMs) has emerged as a highly successful approach, with training only a small number of parameters without sa…