71 citations · 143 across the 8 of their papers we have counts for
11 papers
Momentum Decoding: Open-ended Text Generation As Graph Exploration
Tian Lan, Yixuan Su, Shuhang Liu +2
Open-ended text generation with autoregressive language models (LMs) is one of the core tasks in natural language processing. However, maximization-based decoding methods (e.g., gr…
An Empirical Study On Contrastive Search And Contrastive Decoding For Open-ended Text Generation
Yixuan Su, Jialu Xu
In the study, we empirically compare the two recently proposed decoding methods, i.e. Contrastive Search (CS) and Contrastive Decoding (CD), for open-ended text generation. The aut…
From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document Ranking
Yutao Zhu, Jian-Yun Nie, Yixuan Su +3
Contextual information in search sessions is important for capturing users' search intents. Various approaches have been proposed to model user behavior sequences to improve docume…
Language Models Can See: Plugging Visual Controls in Text Generation
Yixuan Su, Tian Lan, Yahui Liu +5
Generative language models (LMs) such as GPT-2/3 can be prompted to generate text with remarkable quality. While they are designed for text-prompted generation, it remains an open…
A Survey on Retrieval-Augmented Text Generation
Huayang Li, Yixuan Su, Deng Cai +2
Recently, retrieval-augmented text generation attracted increasing attention of the computational linguistics community. Compared with conventional generation models, retrieval-aug…
Plan-then-Generate: Controlled Data-to-Text Generation via Planning
Yixuan Su, David Vandyke, Sihui Wang +2
Recent developments in neural networks have led to the advance in data-to-text generation. However, the lack of ability of neural models to control the structure of generated outpu…