Papers with text transfer
Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoders (2024.findings-eacl)
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| Challenge: | Recent work has struggled to achieve consistent results due to the inevitable loss of semantic information in the variational bottleneck and limited control over the decoding mechanism. |
| Approach: | They propose a model that leverages the controllability of VQVAE to guide the self-attention mechanism in Transformer-based VAEs to improve semantic control and generation. |
| Outcome: | The proposed model outperforms existing state-of-the-art VAE models in terms of control and preservation of semantic information across different tasks. |
Unsupervised Text Style Transfer for Controllable Intensity (2026.findings-eacl)
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| Challenge: | Unsupervised Text Style Transfer (UTST) aims to transfer the stylistic properties of a given text without parallel text pairs. |
| Approach: | They propose a SFT-then-PPO paradigm to fine-tune an LLM with parallel data and reward functions for distinguishing stylistic intensity in hierarchical levels. |
| Outcome: | The proposed system can transfer stylistic properties without parallel text pairs even for adjacent levels of intensity. |