Researcher — paper.dinq.me

2026 顶会论文

作者位次 #6/7ICLR 2026Poster· General Machine Learning / Transfer, Multitask and Meta-learning

Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models

Van Cuong Pham · Anh Hoang · Cuong Nguyen · Trung Le · Dinh Q. Phung · Gustavo Carneiro · Thanh-Toan Do

强化学习与后训练效率与系统OpenReview

作者位次 #6/8CVPR 2026Poster· Computer Vision & Pattern Recognition

TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model

Ao Li · Yuxiang Duan · Jinghui Zhang · Congbo Ma · Yutong Xie · Gustavo Carneiro · Mohammad Yaqub · Hu Wang

效率与系统多模态OpenReview 项目页

作者位次 #5/6ACL 2026Poster· Natural Language Processing

Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models

Cuong Pham · Anh Dung Hoang · Cuong C. Nguyen · Trung Le · Gustavo Carneiro · Thanh-Toan Do

摘要

Large language models (LLMs) have advanced natural language processing, but their massive parameter counts create computational and memory challenges during deployment. Post-training quantization (PTQ) has emerged as a promising approach to mitigate these challenges. While existing PTQ methods ca...

效率与系统强化学习与后训练检索与知识OpenReview 项目页

作者位次 #6/6AAAI 2026Poster· Artificial Intelligence

Coverage-Constrained Human-AI Cooperation with Multiple Experts

Zheng Zhang · Cuong C. Nguyen · Kevin Wells · Thanh-Toan Do · David Rosewarne · Gustavo Carneiro

社会与人本OpenReview

Gustavo Carneiro

获取完整研究档案

联系方式

2026 顶会论文

Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models

TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model

Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models

Coverage-Constrained Human-AI Cooperation with Multiple Experts

常见合作者