3 citations · 4 across the 4 of their papers we have counts for
4 papers
`Keep it Together': Enforcing Cohesion in Extractive Summaries by Simulating Human Memory
Ronald Cardenas, Matthias Galle, Shay B. Cohen
Extractive summaries are usually presented as lists of sentences with no expected cohesion between them. In this paper, we aim to enforce cohesion whilst controlling for informativ…
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…
Unsupervised Extractive Summarization by Human Memory Simulation
Ronald Cardenas, Matthias Galle, Shay B. Cohen
Summarization systems face the core challenge of identifying and selecting important information. In this paper, we tackle the problem of content selection in unsupervised extracti…
A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages
Ronald Cardenas, Ying Lin, Heng Ji +1
Unsupervised part of speech (POS) tagging is often framed as a clustering problem, but practical taggers need to \textit{ground} their clusters as well. Grounding generally require…