1 citations · 1 across the 4 of their papers we have counts for
4 papers
GPrune-LLM: Generalization-Aware Structured Pruning for Large Language Models
Xiaoyun Liu, Divya Saxena, Jiannong Cao +3
Structured pruning is widely applied to compress large language models (LLMs), but its performance depends heavily on how neuron importance is estimated. Most existing methods rely…
Overcoming Growth-Induced Forgetting in Task-Agnostic Continual Learning
Yuqing Zhao, Jiannong Cao, Divya Saxena +4
In continual learning (CL), model growth enhances adaptability to new data. However, when model growth is applied improperly, especially in task-agnostic CL, where the entire grown…
NASPrecision: Neural Architecture Search-Driven Multi-Stage Learning for Surface Roughness Prediction in Ultra-Precision Machining
Penghui Ruan, Divya Saxena, Jiannong Cao +3
Accurate surface roughness prediction is critical for ensuring high product quality, especially in areas like manufacturing and aerospace, where the smallest imperfections can comp…
MGAS: Multi-Granularity Architecture Search for Trade-Off Between Model Effectiveness and Efficiency
Xiaoyun Liu, Divya Saxena, Jiannong Cao +2
Neural architecture search (NAS) has gained significant traction in automating the design of neural networks. To reduce search time, differentiable architecture search (DAS) refram…