Papers by Jeremias Bohn
Adaptive Parameter Compression for Language Models (2025.findings-naacl)
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| Challenge: | Adaptive parameter compression is a new approach to improve NLP models . the current algorithm is based on a single parameter, but it is not scalable. |
| Approach: | They propose a hardware-independent compression strategy that extends the weight-squeezing approach by introducing compression biases and weights. |
| Outcome: | The proposed compression strategy outperforms DistilBERT base models while being significantly more efficient. |