297 citations · 3.3k across the 61 of their papers we have counts for
6 papers · 1 filter
Concise and Precise Context Compression for Tool-Using Language Models
Yang Xu, Yunlong Feng, Honglin Mu +9
Through reading the documentation in the context, tool-using language models can dynamically extend their capability using external tools. The cost is that we have to input lengthy…
UCorrect: An Unsupervised Framework for Automatic Speech Recognition Error Correction
Jiaxin Guo, Minghan Wang, Xiaosong Qiao +9
Error correction techniques have been used to refine the output sentences from automatic speech recognition (ASR) models and achieve a lower word error rate (WER). Previous works u…
Non-autoregressive Streaming Transformer for Simultaneous Translation
Zhengrui Ma, Shaolei Zhang, Shoutao Guo +3
Simultaneous machine translation (SiMT) models are trained to strike a balance between latency and translation quality. However, training these models to achieve high quality while…
RenewNAT: Renewing Potential Translation for Non-Autoregressive Transformer
Pei Guo, Yisheng Xiao, Juntao Li +1
Non-autoregressive neural machine translation (NAT) models are proposed to accelerate the inference process while maintaining relatively high performance. However, existing NAT mod…
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation
Chulun Zhou, Yunlong Liang, Fandong Meng +5
Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performa…
Diformer: Directional Transformer for Neural Machine Translation
Minghan Wang, Jiaxin Guo, Yuxia Wang +8
Autoregressive (AR) and Non-autoregressive (NAR) models have their own superiority on the performance and latency, combining them into one model may take advantage of both. Current…