3 papers
cs.CV2026
APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning
Sadegh Jafari, Mohiuddin Bilwal, Fan Zhou +2
Modern deep neural networks achieve strong performance, but their scale makes them costly and slow, especially on resource-constrained edge devices. Pruning and quantization addres…
cs.LG2025
ProfilingAgent: Profiling-Guided Agentic Reasoning for Adaptive Model Optimization
Sadegh Jafari, Aishwarya Sarkar, Mohiuddin Bilwal +1
Foundation models face growing compute and memory bottlenecks, hindering deployment on resource-limited platforms. While compression techniques such as pruning and quantization are…
cs.CV2025
SuperSAM: Crafting a SAM Supernetwork via Structured Pruning and Unstructured Parameter Prioritization
Waqwoya Abebe, Sadegh Jafari, Sixing Yu +6
Neural Architecture Search (NAS) is a powerful approach of automating the design of efficient neural architectures. In contrast to traditional NAS methods, recently proposed one-sh…