no code implementations • 22 Mar 2024 • Yunqi Zhu, Xuebing Yang, Yuanyuan Wu, Wensheng Zhang
Autoregressive decoding strategy is a commonly used method for text generation tasks with pre-trained language models, while early-exiting is an effective approach to speedup the inference stage.
1 code implementation • 15 May 2023 • Yunqi Zhu, Xuebing Yang, Yuanyuan Wu, Wensheng Zhang
The increasing size of language models raises great research interests in parameter-efficient fine-tuning such as LoRA that freezes the pre-trained model, and injects small-scale trainable parameters for multiple downstream tasks (e. g., summarization, question answering and translation).
no code implementations • 8 Feb 2023 • Yunqi Zhu, Xuebing Yang, Yuanyuan Wu, Wensheng Zhang
This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50K, 16K and 378K pairs of report and summary that are derived from MIMIC-III, respectively.
no code implementations • 27 Apr 2022 • Xichao Zhan, YiWen Chen, Feng Shu, Xin Cheng, Yuanyuan Wu, Qi Zhang, Yifang Li, Peng Zhang
In the proposed Max-RP-QI, a quadratic interpolation scheme is adopted to interpolate the three DOA values corresponding to the largest three receive powers of Max-RP.
1 code implementation • 8 Feb 2022 • Yunqi Zhu, Xuebing Yang, Yuanyuan Wu, Mingjin Zhu, Wensheng Zhang
ROUGE is a standard automatic evaluation metric based on n-grams for sequence-to-sequence tasks, while cross-entropy loss is an essential objective of neural network language model that optimizes at a unigram level.
1 code implementation • 3 Mar 2021 • Honggang Chen, Xiaohai He, Linbo Qing, Yuanyuan Wu, Chao Ren, Ce Zhu
More specifically, this review covers the critical publically available datasets and assessment metrics for RSISR, and four major categories of RSISR methods, namely the degradation modeling-based RSISR, image pairs-based RSISR, domain translation-based RSISR, and self-learning-based RSISR.
no code implementations • 30 Jun 2015 • Yuanyuan Wu, Xiaohai He, Byeongkeun Kang, Haiying Song, Truong Q. Nguyen
This letter presents a novel approach to extract reliable dense and long-range motion trajectories of articulated human in a video sequence.