Research map / Probabilistic and scientific modeling / Variational and generative sampling
Paraphrase Generation with Latent Bag of Words
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add a predicted latent BOW plan to guide decoding | LSTM seq2seq · Quora | BLEU-4: 24.89 -> 26.17 | Helped |
| Add a predicted latent BOW plan to guide decoding | LSTM seq2seq · MSCOCO | BLEU-4: 23.66 -> 25.27 | Helped |
| Use the target BOW during generation | LBOW · Quora | BLEU-4: 26.17 -> 49.47 | Helped |
| Use the target BOW during generation | LBOW · MSCOCO | BLEU-4: 25.27 -> 52.64 | Helped |
| Use Gumbel sampling instead of top-k selection for the BOW (ablation) | LBOW · Quora | BLEU-4: 26.17 -> 26.14 | No clear effect |
| Use Gumbel sampling instead of top-k selection for the BOW (ablation) | LBOW · MSCOCO | BLEU-4: 25.27 -> 24.98 | No clear effect |
| Stop gradients from the decoder to the encoder (ablation) | LBOW · Quora | BLEU-4: 26.17 -> 10.36 | Hurt |
| Stop gradients from the decoder to the encoder (ablation) | LBOW · MSCOCO | BLEU-4: 25.27 -> 9.28 | Hurt |
| Add target-BOW supervision to the latent BOW predictor | LBOW · Quora and MSCOCO | generation performance | Helped |
Closest papers by meaning
- Latent Template Induction with Gumbel-CRFs (NeurIPS 2020 · similarity 0.89)
- A Deep Generative Framework for Paraphrase Generation (AAAI 2018 · similarity 0.88)
- Unsupervised Text Generation by Learning from Search (NeurIPS 2020 · similarity 0.86)
- Compressed and Smooth Latent Space for Text Diffusion Modeling (NeurIPS 2025 · similarity 0.86)
- The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation (ICLR 2025 · similarity 0.85)
- Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models (NeurIPS 2024 · similarity 0.84)
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