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Probing Product Description Generation via Posterior Distillation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use APDT instead of KOBE | product description generation · Clothes&Shoes | ROUGE-L: 19.07 -> 20.41 | Helped |
| use APDT instead of KOBE | product description generation · Digital | ROUGE-L: 18.97 -> 19.95 | Helped |
| use APDT instead of KOBE | product description generation · Homing | ROUGE-L: 18.72 -> 19.68 | Helped |
| add a copy mechanism (ablation) | APDT · Clothes&Shoes | ROUGE-L: 19.13 -> 20.41 | Helped |
| add posterior distillation from reviews (ablation) | APDT · Clothes&Shoes | ROUGE-L: 18.56 -> 20.41 | Helped |
| add coherence-enhanced loss (ablation) | APDT · Clothes&Shoes | ROUGE-L: 19.87 -> 20.41 | Helped |
| add the copy mechanism, posterior distillation, and CoE loss together (ablation) | APDT · Clothes&Shoes | ROUGE-L: 17.95 -> 20.41 | Helped |
| distill from the 5-th or 6-th review encoder layer rather than a shallow layer (ablation) | APDT posterior distillation · Clothes&Shoes validation | ROUGE-L | Mixed |
| increase the coherence weight β up to 0.4, then increase it further (ablation) | APDT CoE loss · JDPDG validation | ROUGE-L | Mixed |
Closest papers by meaning
- Aspect-Aware Multimodal Summarization for Chinese E-Commerce Products (AAAI 2020 · similarity 0.84)
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