3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
QuRL: Efficient Reinforcement Learning with Quantized Rollout
Yuhang Li, Reena Elangovan, Xin Dong +2
Reinforcement learning with verifiable rewards (RLVR) has become a trending paradigm for training reasoning large language models (LLMs). However, due to the autoregressive decodin…
LO-BCQ: Block Clustered Quantization for 4-bit (W4A4) LLM Inference
Reena Elangovan, Charbel Sakr, Anand Raghunathan +1
Post-training quantization (PTQ) is a promising approach to reducing the storage and computational requirements of large language models (LLMs) without additional training cost. Re…
Ax-BxP: Approximate Blocked Computation for Precision-Reconfigurable Deep Neural Network Acceleration
Reena Elangovan, Shubham Jain, Anand Raghunathan
Precision scaling has emerged as a popular technique to optimize the compute and storage requirements of Deep Neural Networks (DNNs). Efforts toward creating ultra-low-precision (s…