Which LoRA? An Empirical Study on the Effectiveness of LoRA Techniques During Multilingual Instruction Tuning
Quick Answer
This paper shows that An empirical study reveals that advanced LoRA variants do not outperform basic LoRA in multilingual instruction tuning, showing no significant benefits in cross-lingual transfer or knowledge retention across diverse datasets.
Quick Take
An empirical study reveals that advanced LoRA variants do not outperform basic LoRA in multilingual instruction tuning, showing no significant benefits in cross-lingual transfer or knowledge retention across diverse datasets. Hidden embeddings analysis indicates similar layer-wise language representation across different LoRA techniques, questioning the architectural novelty's impact on adaptation.
Key Points
- No significant advantage of advanced LoRA variants over basic LoRA in multilingual tuning.
- Study involved experiments on two datasets across diverse target languages.
- Layer-wise language representation remains similar across different LoRA techniques.
- Architectural novelty of LoRA may not enhance cross-lingual adaptation.
Paper Resources
Article Excerpt
From source RSS / original summaryarXiv:2606. 10428v1 Announce Type: new Abstract: We investigate whether commonly available LoRA variants have an advantage over basic LoRA in multilingual instruction tuning. Experiments involving LoRA and four other variants on two datasets across diverse target languages show that there is no significant advantage in using more complex LoRA variants instead of basic LoRA, with respect to balancing cross-lingual transfer and knowledge retention.
An analysis of hidden embeddings reveal that layer-wise language representation remains largely similar across LLMs fine-tuned with different LoRA techniques, suggesting that architectural novelty of LoRA techniques may not translate into better cross-lingual adaptation.
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