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20232026
most citedThe Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2026★ 1 cited

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

Redacted by arXiv

This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…

cs.LG2025

RepLoRA: Reparameterizing Low-Rank Adaptation via the Perspective of Mixture of Experts

Tuan Truong, Chau Nguyen, Huy Nguyen +3

Low-rank Adaptation (LoRA) has emerged as a powerful method for fine-tuning large-scale foundation models. Despite its popularity, the theoretical understanding of LoRA has remaine…

cs.LG2025

On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation

Nghiem T. Diep, Huy Nguyen, Chau Nguyen +5

The LLaMA-Adapter has recently emerged as an efficient fine-tuning technique for LLaMA models, leveraging zero-initialized attention to stabilize training and enhance performance.…

cs.LG2025

Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts

Minh Le, Anh Nguyen, Huy Nguyen +3

Visual Prompt Tuning (VPT) has proven effective for parameter-efficient adaptation of pre-trained vision models to downstream tasks by inserting task-specific learnable prompt toke…

cs.CV2024

UlcerGPT: A Multimodal Approach Leveraging Large Language and Vision Models for Diabetic Foot Ulcer Image Transcription

Reza Basiri, Ali Abedi, Chau Nguyen +2

Diabetic foot ulcers (DFUs) are a leading cause of hospitalizations and lower limb amputations, placing a substantial burden on patients and healthcare systems. Early detection and…

cs.LG2024★ 1 cited

Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts

Minh Le, Chau Nguyen, Huy Nguyen +3

Prompt-based techniques, such as prompt-tuning and prefix-tuning, have gained prominence for their efficiency in fine-tuning large pre-trained models. Despite their widespread adop…

cs.LG2023

Real-Time Magnetic Tracking and Diagnosis of COVID-19 via Machine Learning

Dang Nguyen, Phat K. Huynh, Vinh Duc An Bui +10

The COVID-19 pandemic underscored the importance of reliable, noninvasive diagnostic tools for robust public health interventions. In this work, we fused magnetic respiratory sensi…