2 citations · 3 across the 4 of their papers we have counts for
4 papers
LFM2 Technical Report
Alexander Amini, Anna Banaszak, Harold Benoit +30
We present LFM2, a family of Liquid Foundation Models designed for efficient on-device deployment and strong task capabilities. Using hardware-in-the-loop architecture search under…
Training-Free Tokenizer Transplantation via Orthogonal Matching Pursuit
Charles Goddard, Fernando Fernandes Neto
We present a training-free method to transplant tokenizers in pretrained large language models (LLMs) by reconstructing unseen token embeddings via Orthogonal Matching Pursuit (OMP…
Domain Adaptation of Llama3-70B-Instruct through Continual Pre-Training and Model Merging: A Comprehensive Evaluation
Shamane Siriwardhana, Mark McQuade, Thomas Gauthier +8
We conducted extensive experiments on domain adaptation of the Meta-Llama-3-70B-Instruct model on SEC data, exploring its performance on both general and domain-specific benchmarks…
Spectrum: Targeted Training on Signal to Noise Ratio
Eric Hartford, Lucas Atkins, Fernando Fernandes Neto +1
Efficiently post-training large language models remains a challenging task due to the vast computational resources required. We present Spectrum, a method that accelerates LLM trai…