Papers with denoising neural network

2 papers
Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback (2022.findings-naacl)

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Challenge: Existing work on news recommendation only used positive and negative implicit feedback and suffered from the noise impact.
Approach: They propose a denoising neural network for news recommendation with positive and negative implicit feedback, named DRPN.
Outcome: The proposed method improves on the real-world large-scale dataset.
Let’s Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Models (2024.lrec-main)

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Challenge: Empirical evaluations conducted on eight benchmark datasets underscore the compelling advantages offered by DiffusionABSA when compared against robust baseline models.
Approach: They propose a diffusion model which extracts aspects step by step and learns a denoising process that progressively restores them in a reverse manner.
Outcome: Empirical evaluations on eight benchmark datasets underscore the compelling advantages offered by DiffusionABSA when compared against robust baseline models.

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