Papers by Yixing Li
Continuous Speech Tokenizer in Text To Speech (2025.findings-naacl)
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| Challenge: | Autoregressive modeling is a common method for processing language sequences and is effective in token prediction. |
| Approach: | They propose a text-to-speech model based on continuous speech tokens and a continuous tokenizer for speech compression. |
| Outcome: | The proposed model has better continuity and higher estimated Mean Opinion Scores (MoS) this is attributed to better information preservation rate across low and high frequencies in the frequency domain. |
Enhancing One-Shot Pruned Pre-trained Language Models through Sparse-Dense-Sparse Mechanism (2025.coling-main)
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Guanchen Li, Xiandong Zhao, Lian Liu, Zeping Li, Yixing Xu, Dong Li, Lu Tian, Jie He, Ashish Sirasao, Emad Barsoum
| Challenge: | Pre-trained language models (PLMs) are robust in contextual understanding but their considerable size incurs significant computational and storage costs. |
| Approach: | They propose a Sparse-Dense-Sparse pruning framework to prune PLMs . they prune less critical connections using conventional pruning methods . |
| Outcome: | The proposed pruning framework outperforms SparseGPT and Wanda under identical sparsity. |