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cs.LG2026
REAL-Q: E2E LLM Quantization via Dynamic Gradient Descent
Qian Zhang, Yaoming Li, Zhewen Tan +9
Post-training quantization (PTQ) is essential for deploying large language models (LLMs) under strict resource constraints. State-of-the-art PTQ methods quantize each layer with a…
cs.LG2024★ 1 cited
The Impact of Quantization and Pruning on Deep Reinforcement Learning Models
Heng Lu, Mehdi Alemi, Reza Rawassizadeh
Deep reinforcement learning (DRL) has achieved remarkable success across various domains, such as video games, robotics, and, recently, large language models. However, the computat…