Papers with unsupervised opinion summarization
Convex Aggregation for Opinion Summarization (2021.findings-emnlp)
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| Challenge: | Recent advances in text autoencoders have significantly improved the quality of the latent space, allowing models to generate consistent text from aggregated latent vectors. |
| Approach: | They develop a framework which searches input-output word overlap for latent vector aggregation. |
| Outcome: | The proposed framework improves the quality of the latent space and establishes state-of-the-art performance on two opinion summarization benchmarks. |
Disentangling Text Representation With Counter-Template For Unsupervised Opinion Summarization (2023.findings-acl)
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| Challenge: | Existing approaches for unsupervised opinion summarization are based on reconstruction model, but selection is too coarse as not all information in each input is equally essential for the summary. |
| Approach: | They propose a framework for unsupervised opinion summarization based on text representation disentanglement with counter-template. |
| Outcome: | The proposed framework outperforms the state-of-the-art models on quality and stability on two benchmark datasets. |
Attributable and Scalable Opinion Summarization (2023.acl-long)
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| Challenge: | Existing methods for opinion summarization encode sentences from customer reviews into a hierarchical discrete latent space. |
| Approach: | They propose a method that encodes customer reviews into a hierarchical discrete latent space and then identifies common opinions based on their frequency. |
| Outcome: | The proposed method generates summaries that are more informative than previous work and more grounded in the input reviews. |