83 citations · 264 across the 31 of their papers we have counts for
13 papers · 1 filter
Plug-and-Play Recipe Generation with Content Planning
Yinhong Liu, Yixuan Su, Ehsan Shareghi +1
Recent pre-trained language models have shown promising capabilities in generating fluent and realistic natural language text. However, generating multi-sentence text with global c…
DePlot: One-shot visual language reasoning by plot-to-table translation
Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno +7
Visual language such as charts and plots is ubiquitous in the human world. Comprehending plots and charts requires strong reasoning skills. Prior state-of-the-art (SOTA) models req…
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering
Fangyu Liu, Francesco Piccinno, Syrine Krichene +6
Visual language data such as plots, charts, and infographics are ubiquitous in the human world. However, state-of-the-art vision-language models do not perform well on these data.…
On the Effectiveness of Parameter-Efficient Fine-Tuning
Zihao Fu, Haoran Yang, Anthony Man-Cho So +3
Fine-tuning pre-trained models has been ubiquitously proven to be effective in a wide range of NLP tasks. However, fine-tuning the whole model is parameter inefficient as it always…
How to tackle an emerging topic? Combining strong and weak labels for Covid news NER
Aleksander Ficek, Fangyu Liu, Nigel Collier
Being able to train Named Entity Recognition (NER) models for emerging topics is crucial for many real-world applications especially in the medical domain where new topics are cont…
Contrastive Search Is What You Need For Neural Text Generation
Yixuan Su, Nigel Collier
Generating text with autoregressive language models (LMs) is of great importance to many natural language processing (NLP) applications. Previous solutions for this task often prod…