Methods › General › Ternarization › Ternary Weight Splitting
Ternary Weight Splitting
Introduced by Haoli Bai et al. in BinaryBERT: Pushing the Limit of BERT Quantization
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Ternary Weight Splitting is a ternarization approach used in BinaryBERT that exploits the flatness of ternary loss landscape as the optimization proxy of the binary model. We first train the half-sized ternary BERT to convergence, and then split both the latent full-precision weight 𝐰ᵗ and quantized 𝐰̂ᵗ to their binary counterparts 𝐰₁ᵇ, 𝐰₂ᵇ and 𝐰̂₁ᵇ, 𝐰̂₂ᵇ via the TWS operator. To inherit the performance of the ternary model after splitting, the TWS operator requires the splitting equivalency (i.e., the same output given the same input):
𝐰ᵗ=𝐰₁ᵇ+𝐰₂ᵇ, 𝐰̂ᵗ=𝐰̂₁ᵇ+𝐰̂₂ᵇ
While solution to the above equation is not unique, we constrain the latent full-precision weights after splitting 𝐰₁ᵇ, 𝐰₂ᵇ to satisfy 𝐰ᵗ=𝐰₁ᵇ+𝐰₂ᵇ. See the paper for more details.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Co-Designing Binarized Transformer and Hardware Accelerator for Efficient End-to-End Edge Deployment 16 Jul 2024 · 0 repositories · arXiv:2407.12070
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BinaryBERT: Pushing the Limit of BERT Quantization 31 Dec 2020 · 1 repository · arXiv:2012.15701Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
Tasks archive 2025-07-28
4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Quantization | 2 |
| Binarization | 1 |
| Model Compression | 1 |
| Scheduling | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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