Candidate Soups: Fusing Candidate Results Improves Translation Quality
for Non-Autoregressive Translation

Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translation

27 January 2023

Papers citing "Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translation"

10 / 10 papers shown

Title
PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustment Zequan Liu Yi Zhao Ming Tan Wei Zhu Aaron Xuxiang Tian 43 0 0 03 Feb 2025
MiLoRA: Efficient Mixture of Low-Rank Adaptation for Large Language Models Fine-tuning Jingfan Zhang Yi Zhao Dan Chen Xing Tian Huanran Zheng Wei Zhu MoE 40 12 0 23 Oct 2024
IAPT: Instruction-Aware Prompt Tuning for Large Language Models Wei-wei Zhu Aaron Xuxiang Tian Congrui Yin Yuan Ni Xiaoling Wang Guotong Xie 48 0 0 28 May 2024
ALoRA: Allocating Low-Rank Adaptation for Fine-tuning Large Language Models Zequan Liu Jiawen Lyn Wei-wei Zhu Xing Tian Yvette Graham OffRL 40 10 0 24 Mar 2024
Overview of the PromptCBLUE Shared Task in CHIP2023 Wei-wei Zhu Xiaoling Wang Mosha Chen Buzhou Tang LM&MA ELM 39 7 0 29 Dec 2023
PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain Wei-wei Zhu Xiaoling Wang Huanran Zheng Mosha Chen Buzhou Tang ELM LM&MA 21 33 0 22 Oct 2023
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Chenyang Huang Hao Zhou Osmar R. Zaïane Lili Mou Lei Li 92 59 0 14 Oct 2021
AligNART: Non-autoregressive Neural Machine Translation by Jointly Learning to Estimate Alignment and Translate Jongyoon Song Sungwon Kim Sungroh Yoon 74 37 0 14 Sep 2021
Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation Yongchang Hao Shilin He Wenxiang Jiao Zhaopeng Tu Michael Lyu Xing Wang 98 28 0 24 Oct 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015