Guangxuan Xiao

According to our database, Guangxuan Xiao authored at least 12 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training.

Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang

Proc. VLDB Endow., February, 2024

BitDelta: Your Fine-Tune May Only Be Worth One Bit.

James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai

CoRR, 2024

InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory.

Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Song Han, Maosong Sun

CoRR, 2024

2023

Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-level Backdoor Attacks.

Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, Maosong Sun

Mach. Intell. Res., April, 2023

Efficient Streaming Language Models with Attention Sinks.

Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis

CoRR, 2023

FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention.

Guangxuan Xiao, Tianwei Yin, William T. Freeman, Frédo Durand, Song Han

CoRR, 2023

Offsite-Tuning: Transfer Learning without Full Model.

Guangxuan Xiao, Ji Lin, Song Han

CoRR, 2023

ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training.

Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang

CoRR, 2023

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, Song Han

Proceedings of the International Conference on Machine Learning, 2023

2022

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models.

Guangxuan Xiao, Ji Lin, Mickaël Seznec, Julien Demouth, Song Han

CoRR, 2022

Sparse and Local Networks for Hypergraph Reasoning.

Guangxuan Xiao, Leslie Pack Kaelbling, Jiajun Wu, Jiayuan Mao

Proceedings of the Learning on Graphs Conference, 2022

2021

Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks.

Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, Maosong Sun

CoRR, 2021