Papers with monolingual applications

2 papers
On the Limitations of Language-targeted Pruning: Investigating the Calibration Language Impact in Multilingual LLM Pruning (2026.tacl-1)

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Challenge: Recent advances in large language model pruning have shown high predictive performance in post-training settings.
Approach: They conduct an empirical study on the performance and internal representation changes associated with pruning multilingual models for monolingual applications.
Outcome: The proposed pruning methods retain perplexity and yield high signal-to-noise ratios, but not consistently improve downstream tasks.
The Impact of Positional Encodings on Multilingual Compression (2021.emnlp-main)

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Challenge: Several modifications have been proposed to improve monolingual language models, but none of them result in better multilingual models.
Approach: They propose to add positional encodings to token embeddings to preserve word-order information in a non-autoregressive setting.
Outcome: The proposed modifications tend to improve monolingual models, but none improve multilingual models.

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