Jinghong Tan, Zhian Liu, Kun Guo, Mingxiong Zhao: Long-Term Client Selection for Federated Learning with Non-IID Data: A Truthful Auction Approach https://arxiv.org/abs/2508.09181 https://arxiv.org/pdf/2508.09181 https://arxiv.org/html/2508.09181
August 14, 2025 at 6:33 AM
Jinghong Tan, Zhian Liu, Kun Guo, Mingxiong Zhao: Long-Term Client Selection for Federated Learning with Non-IID Data: A Truthful Auction Approach https://arxiv.org/abs/2508.09181 https://arxiv.org/pdf/2508.09181 https://arxiv.org/html/2508.09181
This #WorldBrainDay, we’re spotlighting the groundbreaking MEG Center at #qualcomminstitute.
We’re 1 of only ~20 U.S. centers using MEG—a noninvasive brain imaging tech that maps activity with unmatched precision.
Curious how it works? Read more about it at bit.ly/qi-meg!
We’re 1 of only ~20 U.S. centers using MEG—a noninvasive brain imaging tech that maps activity with unmatched precision.
Curious how it works? Read more about it at bit.ly/qi-meg!
Visualizing the Invisible with MEG (video and transcript) - Qualcomm Institute
In this interview, the directors of the new Qualcomm Institute (QI) Magnetoencephalography (MEG) Center Roland Lee, M.D, and Mingxiong Huang, Ph.D., speak on topics from the underpinnings of the advan...
bit.ly
July 22, 2025 at 7:59 PM
This #WorldBrainDay, we’re spotlighting the groundbreaking MEG Center at #qualcomminstitute.
We’re 1 of only ~20 U.S. centers using MEG—a noninvasive brain imaging tech that maps activity with unmatched precision.
Curious how it works? Read more about it at bit.ly/qi-meg!
We’re 1 of only ~20 U.S. centers using MEG—a noninvasive brain imaging tech that maps activity with unmatched precision.
Curious how it works? Read more about it at bit.ly/qi-meg!
qingxuan isn't bothered by it, heavenly officials heal fast anyway (okay he's a Little spooked but mostly haha wow mingxiong i know youre hungry but please dont eat me in That Sense) but he xuan feels SO BAD
he stops biting even when with hua cheng after that.
he stops biting even when with hua cheng after that.
March 17, 2025 at 4:09 PM
qingxuan isn't bothered by it, heavenly officials heal fast anyway (okay he's a Little spooked but mostly haha wow mingxiong i know youre hungry but please dont eat me in That Sense) but he xuan feels SO BAD
he stops biting even when with hua cheng after that.
he stops biting even when with hua cheng after that.
“Don't worry. Ming-xiong is someone who doesn't even know how to lie.”
While me While
Ming-xiong
#tgcf #shiqingxuan #mingxiong
While me While
Ming-xiong
#tgcf #shiqingxuan #mingxiong
December 27, 2024 at 5:39 PM
“Don't worry. Ming-xiong is someone who doesn't even know how to lie.”
While me While
Ming-xiong
#tgcf #shiqingxuan #mingxiong
While me While
Ming-xiong
#tgcf #shiqingxuan #mingxiong
Beefleaf 🍖🍃
#heavenofficialsblessing #tgcf #tgcffanart #beefleaf #shiqingxuan #lordwindmaster #hexuan #mingyi #mingxiong
#heavenofficialsblessing #tgcf #tgcffanart #beefleaf #shiqingxuan #lordwindmaster #hexuan #mingyi #mingxiong
November 4, 2024 at 1:01 AM
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
July 4, 2024 at 10:02 AM
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
June 10, 2024 at 12:01 PM
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
February 19, 2024 at 8:01 AM
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
February 19, 2024 at 5:09 AM
Yuanzhen Xie, Xinzhou Jin, Tao Xie, MingXiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, ChengXiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
https://arxiv.org/abs/2402.10671