65 citations · 130 across the 11 of their papers we have counts for
7 papers · 1 filter
Does deep learning always outperform simple linear regression in optical imaging?
Shuming Jiao, Yang Gao, Jun Feng +2
Deep learning has been extensively applied in many optical imaging applications in recent years. Despite the success, the limitations and drawbacks of deep learning in optical imag…
MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
Wei Zhao, Maxime Peyrard, Fei Liu +3
A robust evaluation metric has a profound impact on the development of text generation systems. A desirable metric compares system output against references based on their semantic…
Better Rewards Yield Better Summaries: Learning to Summarise Without References
Florian Böhm, Yang Gao, Christian M. Meyer +3
Reinforcement Learning (RL) based document summarisation systems yield state-of-the-art performance in terms of ROUGE scores, because they directly use ROUGE as the rewards during…
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation
Yang Gao, Christian M. Meyer, Mohsen Mesgar +1
Document summarisation can be formulated as a sequential decision-making problem, which can be solved by Reinforcement Learning (RL) algorithms. The predominant RL paradigm for sum…
Preference-based Interactive Multi-Document Summarisation
Yang Gao, Christian M. Meyer, Iryna Gurevych
Interactive NLP is a promising paradigm to close the gap between automatic NLP systems and the human upper bound. Preference-based interactive learning has been successfully applie…
Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation
Ori Shapira, David Gabay, Yang Gao +5
Conducting a manual evaluation is considered an essential part of summary evaluation methodology. Traditionally, the Pyramid protocol, which exhaustively compares system summaries…