activity
20172024
most citedIncorporating BERT into Parallel Sequence Decoding with Adapters

40 citations · 188 across the 22 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.CV2023★ 2 cited

GAIA: Zero-shot Talking Avatar Generation

Tianyu He, Junliang Guo, Runyi Yu +10

Zero-shot talking avatar generation aims at synthesizing natural talking videos from speech and a single portrait image. Previous methods have relied on domain-specific heuristics…

cs.CL2023★ 35 cited

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Qingyan Guo, Rui Wang, Junliang Guo +6

Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted prompts that often demand substantial human effort. To automate this process, in this paper,…

cs.AI2023★ 1 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.CL2023★ 5 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.CL2023

ResiDual: Transformer with Dual Residual Connections

Shufang Xie, Huishuai Zhang, Junliang Guo +6

Transformer networks have become the preferred architecture for many tasks due to their state-of-the-art performance. However, the optimal way to implement residual connections in…

cs.CL2023★ 23 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…