From Moments to Milestones: Incremental Timeline Summarization Leveraging Large Language Models (2024.acl-long)
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| Challenge: | Prior work on timeline summarization has neglected the potential synergy between the two forms of timelines. |
| Approach: | They propose a timeline summarization approach that leverages large language models to generate both event and topic timelines. |
| Outcome: | The proposed approach outperforms the best existing approaches in four TLS benchmarks. |
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| Challenge: | Prior approaches to TLS focus on extractive methods, which generate extractive timelines . a study with human judges shows that our abstractive system also produces output that is easy to read and understand. |
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Multi-TimeLine Summarization (MTLS): Improving Timeline Summarization by Generating Multiple Summaries (2021.acl-long)
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| Challenge: | Existing work on Time-Line Summarization (TLS) has focused on improving the performance of summarization but its drawbacks are as follows: a homogeneous dataset makes it hard to generalize; output is usually a single timeline regardless of the size and complexity of the input dataset. |
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Temporal reasoning for timeline summarisation in social media (2025.acl-long)
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| Challenge: | Existing temporal reasoning datasets focus on pair-wise event relationships. |
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Examining the State-of-the-Art in News Timeline Summarization (2020.acl-main)
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| Challenge: | Existing work on news timeline summarization (TLS) has left an unclear picture of how well it is currently solved and how it can be approached. |
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Dataset Reproducibility and IR Methods in Timeline Summarization (2020.lrec-1)
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| Challenge: | Timeline summarization (TLS) generates a dated overview of real-world events based on event-specific corpora. |
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| Challenge: | Using hierarchical Dirichlet processes, we characterize news articles associated with key events from news streams. |
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| Challenge: | Existing timeline summarizations lack flexibility to meet diverse granularity needs . a fine-grained timeline showing the technical details is preferred for news topics . |
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R2A-TLS: Reflective Retrieval-Augmented Timeline Summarization with Causal-Semantic Integration (2025.findings-emnlp)
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| Challenge: | Existing methods struggle to capture coherent event narratives due to fragmented descriptions . Existing approaches accumulate noise through iterative retrieval strategies that lack relevance evaluation. |
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SUMIE: A Synthetic Benchmark for Incremental Entity Summarization (2025.coling-main)
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| Challenge: | Existing datasets that test incrementally update entity summaries are lacking. |
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