Research Paper#Speech Recognition, Natural Language Processing, Machine Translation🔬 ResearchAnalyzed: Jan 3, 2026 23:55
Rare Word Recognition and Translation Without Fine-Tuning
Published:Dec 26, 2025 06:51
•1 min read
•ArXiv
Analysis
This paper addresses a significant problem in speech-to-text systems: the difficulty of handling rare words. The proposed method offers a training-free alternative to fine-tuning, which is often costly and prone to issues like catastrophic forgetting. The use of task vectors and word-level arithmetic is a novel approach that promises scalability and reusability. The results, showing comparable or superior performance to fine-tuned models, are particularly noteworthy.
Key Takeaways
- •Proposes a training-free method for rare word recognition and translation.
- •Utilizes task vectors and word-level arithmetic for scalability and reusability.
- •Achieves performance comparable to or better than fine-tuned models.
- •Mitigates catastrophic forgetting, a common issue with fine-tuning.
Reference
“The proposed method matches or surpasses fine-tuned models on target words, improves general performance by about 5 BLEU, and mitigates catastrophic forgetting.”