natural-language-processing-8

Timeline Summarization

3260 papers • 126 benchmarks • 313 datasets

Identifying key dates of major events and providing short descriptions of what happened on these dates. (Source: https://www.aclweb.org/anthology/D19-5403/)

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in timeline-summarization-17

Trend

Dataset

Best Model

Actions

MTS

Libraries

i

Use these libraries to find timeline-summarization-17 models and implementations

Datasets

No datasets available.

Subtasks

No subtasks available.

Most implemented papers

A Temporally Sensitive Submodularity Framework for Timeline Summarization

K. Markert, Sebastian Martschat•Sun Sep 30 2018

It is shown that MDS optimization models using submodular functions can be adapted to yield well-performing TLS models by designing objective functions and constraints that model the temporal dimension inherent in TLS.

40

Content

0

Paper Graph

Learning towards Abstractive Timeline Summarization

Rui Yan, Shen Gao, Xiuying Chen, Zhangming Chan, Meng-Hsuan Yu, Dongyan Zhao•Wed Jul 31 2019

This paper proposes a memory-based timeline summarization model (MTS), which tends to concisely paraphrase the information in the time-stamped events and achieves the state-of-the-art performance in terms of both automatic and human evaluations.

39 0

Paper Graph

Examining the State-of-the-Art in News Timeline Summarization

D. Ghalandari, Georgiana Ifrim•Tue May 19 2020

This paper compares different TLS strategies using appropriate evaluation frameworks, and proposes a simple and effective combination of methods that improves over the stateof-the-art on all tested benchmarks.

48 0

Paper Graph

Follow the Timeline! Generating Abstractive and Extractive Timeline Summary in Chronological Order

Dongyan Zhao, Rui Yan, Xiuying Chen, Zhangming Chan, Li Mingzhe, Shen Gao, Xin Gao, Xiangliang Zhang•Sun Jan 01 2023

A Unified Timeline Summarizer (UTS) that can generate abstractive and extractive timeline summaries in time order is proposed and achieves state-of-the-art performance in terms of both automatic and human evaluations.

5 0

Paper Graph

Adding a benchmark result helps the community track progress.