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Guangxuan Xiao
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2020 – today
- 2024
- [j2]Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang:
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training. Proc. VLDB Endow. 17(6): 1473-1486 (2024) - [c4]Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis:
Efficient Streaming Language Models with Attention Sinks. ICLR 2024 - [c3]Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han:
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration. MLSys 2024 - [i12]Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Song Han, Maosong Sun:
InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory. CoRR abs/2402.04617 (2024) - [i11]James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai:
BitDelta: Your Fine-Tune May Only Be Worth One Bit. CoRR abs/2402.10193 (2024) - [i10]Wenhao Wu, Yizhong Wang, Guangxuan Xiao, Hao Peng, Yao Fu:
Retrieval Head Mechanistically Explains Long-Context Factuality. CoRR abs/2404.15574 (2024) - [i9]Yujun Lin, Haotian Tang, Shang Yang, Zhekai Zhang, Guangxuan Xiao, Chuang Gan, Song Han:
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving. CoRR abs/2405.04532 (2024) - [i8]Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, Song Han:
Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference. CoRR abs/2406.10774 (2024) - 2023
- [j1]Zhengyan Zhang
, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu
, Yasheng Wang, Xin Jiang, Maosong Sun:
Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-level Backdoor Attacks. Mach. Intell. Res. 20(2): 180-193 (2023) - [c2]Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, Song Han:
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. ICML 2023: 38087-38099 - [i7]Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang
, Jidong Zhai, Zheng Zhang:
ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training. CoRR abs/2301.07482 (2023) - [i6]Guangxuan Xiao, Ji Lin, Song Han:
Offsite-Tuning: Transfer Learning without Full Model. CoRR abs/2302.04870 (2023) - [i5]Guangxuan Xiao, Leslie Pack Kaelbling, Jiajun Wu, Jiayuan Mao:
Sparse and Local Networks for Hypergraph Reasoning. CoRR abs/2303.05496 (2023) - [i4]Guangxuan Xiao, Tianwei Yin, William T. Freeman, Frédo Durand, Song Han:
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention. CoRR abs/2305.10431 (2023) - [i3]Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis:
Efficient Streaming Language Models with Attention Sinks. CoRR abs/2309.17453 (2023) - 2022
- [c1]Guangxuan Xiao, Leslie Pack Kaelbling, Jiajun Wu, Jiayuan Mao:
Sparse and Local Networks for Hypergraph Reasoning. LoG 2022: 34 - [i2]Guangxuan Xiao, Ji Lin, Mickaël Seznec, Julien Demouth, Song Han:
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. CoRR abs/2211.10438 (2022) - 2021
- [i1]Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, Maosong Sun:
Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks. CoRR abs/2101.06969 (2021)
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last updated on 2024-08-08 20:16 CEST by the dblp team
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