most citedA Study on ReLU and Softmax in Transformer

23 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI20231 cited

Retrosynthesis Prediction with Local Template Retrieval

Shufang Xie, Rui Yan, Junliang Guo +3

Retrosynthesis, which predicts the reactants of a given target molecule, is an essential task for drug discovery. In recent years, the machine learing based retrosynthesis methods…

cs.CL2023

Extract and Attend: Improving Entity Translation in Neural Machine Translation

Zixin Zeng, Rui Wang, Yichong Leng +4

While Neural Machine Translation(NMT) has achieved great progress in recent years, it still suffers from inaccurate translation of entities (e.g., person/organization name, locatio…

cs.CL20235 cited

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…

cs.CL202323 cited

A Study on ReLU and Softmax in Transformer

Kai Shen, Junliang Guo, Xu Tan +3

The Transformer architecture consists of self-attention and feed-forward networks (FFNs) which can be viewed as key-value memories according to previous works. However, FFN and tra…

cs.CL2023

N-Gram Nearest Neighbor Machine Translation

Rui Lv, Junliang Guo, Rui Wang +3

Nearest neighbor machine translation augments the Autoregressive Translation~(AT) with -nearest-neighbor retrieval, by comparing the similarity between the token-level context r…

cs.CL2022

A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation

Kexun Zhang, Rui Wang, Xu Tan +4

It is difficult for non-autoregressive translation (NAT) models to capture the multi-modal distribution of target translations due to their conditional independence assumption, whi…