25 citations · 27 across the 4 of their papers we have counts for
4 papers
The Markovian Thinker: Architecture-Agnostic Linear Scaling of Reasoning
Milad Aghajohari, Kamran Chitsaz, Amirhossein Kazemnejad +4
Reinforcement learning (RL) has recently become a strong recipe for training reasoning LLMs that produce long chains of thought (LongCoT). Yet the standard RL "thinking environment…
A Large Scale Investigation of Scaling Limits in Chemical Language Models
Kamran Chitsaz, Roshan Balaji, Quentin Fournier +2
Chemical Language Models (CLMs) are increasingly used in de novo drug design, driven by recent growth in model scale, compute, and dataset size. However, the relationship between d…
Exploring Quantization for Efficient Pre-Training of Transformer Language Models
Kamran Chitsaz, Quentin Fournier, Gonçalo Mordido +1
The increasing scale of Transformer models has led to an increase in their pre-training computational requirements. While quantization has proven to be effective after pre-training…
Acceleration of Convolutional Neural Network Using FFT-Based Split Convolutions
Kamran Chitsaz, Mohsen Hajabdollahi, Nader Karimi +2
Convolutional neural networks (CNNs) have a large number of variables and hence suffer from a complexity problem for their implementation. Different methods and techniques have dev…