Resource-Efficient Pruning for Transformer via Low-Rank Importance Estimation

arXiv:2608.24973 · cs.LG, cs.AI, cs.ET · Submitted 2026-08-25 · Read on arXiv

cs.LG, cs.AI, cs.ET

Submitted: 2026-08-25

Updated: 2026-08-25

Comments: 15 pages, 9 figures

Journal ref: IEEE Transactions on Emerging Topics in Computational Intelligence, 2026

DOI: 10.1109/TETCI.2026.3727362

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Pruning — 154× in this paper · explained in 4 episodes
• Sparsity — 45× in this paper · explained in 4 episodes
• Transformer — 24× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Adaptation — 8× in this paper · explained in 1 episode
• Computational overhead — 6× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• Transformer Models — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Data Augmentation — 3× in this paper · explained in 7 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Perplexity — 3× in this paper · explained in 3 episodes
• Quantization — 3× in this paper · explained in 12 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Activation Function — 2× in this paper · explained in 1 episode
• Feed-Forward Network — 2× in this paper
• Fidelity — 2× in this paper · explained in 2 episodes
• Fisher Information — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Edge AI — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Grouped-Query Attention — 1× in this paper
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Fine-tune BERT for Extractive Summarization
• A Survey on Transformer Compression
• Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models

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