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2020 – today
- 2025
[c27]Yunwei Bai, Ying Kiat Tan, Shiming Chen, Yao Shu, Tsuhan Chen:
FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation. AAAI 2025: 15462-15471- [c26]Chenxing Wei, Yao Shu, Ying Tiffany He, Fei Yu:
Flexora: Flexible Low-Rank Adaptation for Large Language Models. ACL (1) 2025: 14643-14682 - [c25]Qixin Zhang, Wei Huang, Can Jin, Puning Zhao, Yao Shu, Li Shen, Dacheng Tao:
Multinoulli Extension: A Lossless Yet Effective Probabilistic Framework for Subset Selection over Partition Constraints. ICML 2025 - [c24]Yao Shu, Qixin Zhang, Kun He, Zhongxiang Dai:
Refining Adaptive Zeroth-Order Optimization at Ease. ICML 2025 - [c23]Yao Shu, Wenyang Hu, See-Kiong Ng, Bryan Kian Hsiang Low, Fei Richard Yu:
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models. ICML 2025 - [c22]Songbai Tan, Xuerui Qiu, Yao Shu, Gang Xu, Linrui Xu, Xiangyu Xu, Huiping Zhuang, Ming Li, Fei Richard Yu:
WMarkGPT: Watermarked Image Understanding via Multimodal Large Language Models. ICML 2025 - [c21]Yao Shu, Lianyu Zheng, Jinfu Chen, Jifeng Xuan:
Characterizing Logs in Vulnerability Reports: In-Depth Analysis and Security Implications. SANER 2025: 704-715 - [i36]Mingze Kong, Zhiyong Wang, Yao Shu, Zhongxiang Dai:
Meta-Prompt Optimization for LLM-Based Sequential Decision Making. CoRR abs/2502.00728 (2025) - [i35]Yao Shu, Qixin Zhang, Kun He, Zhongxiang Dai:
Refining Adaptive Zeroth-Order Optimization at Ease. CoRR abs/2502.01014 (2025) - [i34]Chenxing Wei, Yao Shu, Mingwen Ou, Ying Tiffany He, Fei Richard Yu:
PAFT: Prompt-Agnostic Fine-Tuning. CoRR abs/2502.12859 (2025) - [i33]Jiahao Qiu, Fulian Xiao, Yimin Wang, Yuchen Mao, Yijia Chen, Xinzhe Juan, Siran Wang, Xuan Qi, Tongcheng Zhang, Zixin Yao, Jiacheng Guo, Yifu Lu, Charles Argon, Jundi Cui, Daixin Chen, Junran Zhou, Shuyao Zhou, Zhanpeng Zhou, Ling Yang, Shilong Liu, Hongru Wang, Kaixuan Huang, Xun Jiang, Yuming Cao, Yue Chen, Yunfei Chen, Zhengyi Chen, Ruowei Dai, Mengqiu Deng, Jiye Fu, Yunting Gu, Zijie Guan, Zirui Huang, Xiaoyan Ji, Yumeng Jiang, Delong Kong, Haolong Li, Jiaqi Li, Ruipeng Li, Tianze Li, Zhuoran Li, Haixia Lian, Mengyue Lin, Xudong Liu, Jiayi Lu, Jinghan Lu, Wanyu Luo, Ziyue Luo, Zihao Pu, Zhi Qiao, Ruihuan Ren, Liang Wan, Ruixiang Wang, Tianhui Wang, Yang Wang, Zeyu Wang, Zihua Wang, Yujia Wu, Zhaoyi Wu, Hao Xin, Weiao Xing, Ruojun Xiong, Weijie Xu, Yao Shu, Xiao Yao, Xiaorui Yang, Yuchen Yang, Nan Yi, Jiadong Yu, Yangyuxuan Yu, Huiting Zeng, Danni Zhang, Yunjie Zhang, Zhaoyu Zhang, Zhiheng Zhang, Xiaofeng Zheng, Peirong Zhou, Linyan Zhong, Xiaoyin Zong, Ying Zhao, Zhenxin Chen, Lin Ding, Xiaoyu Gao, Bingbing Gong, Yichao Li, Yang Liao, Guang Ma, Tianyuan Ma, Xinrui Sun, Tianyi Wang, Han Xia, Ruobing Xian, Gen Ye, Tengfei Yu, Wentao Zhang, Yuxi Wang, Xi Gao, Mengdi Wang:
On Path to Multimodal Historical Reasoning: HistBench and HistAgent. CoRR abs/2505.20246 (2025) - [i32]Junbin Qiu, Zhengpeng Xie, Xiangda Yan, Yongjie Yang, Yao Shu:
Zeroth-Order Optimization is Secretly Single-Step Policy Optimization. CoRR abs/2506.14460 (2025) - [i31]Chenxing Wei, Jiarui Yu, Ying Tiffany He, Hande Dong, Yao Shu, Fei Yu:
ReDit: Reward Dithering for Improved LLM Policy Optimization. CoRR abs/2506.18631 (2025) - [i30]Haotian Wu, Bo Xu, Yao Shu, Menglin Yang, Chengwei Qin:
Thinking with Nothinking Calibration: A New In-Context Learning Paradigm in Reasoning Large Language Models. CoRR abs/2508.03363 (2025) - [i29]Jindong Li, Yali Fu, Li Fan, Jiahong Liu, Yao Shu, Chengwei Qin, Menglin Yang, Irwin King, Rex Ying:
Implicit Reasoning in Large Language Models: A Comprehensive Survey. CoRR abs/2509.02350 (2025) - [i28]Ziye Chen, Chengwei Qin, Yao Shu:
RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning. CoRR abs/2509.07711 (2025) - [i27]Qixin Zhang, Yan Sun, Can Jin, Xikun Zhang, Yao Shu, Puning Zhao, Li Shen, Dacheng Tao:
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives. CoRR abs/2509.22596 (2025) - [i26]Chenxing Wei, Hong Wang, Ying He, Fei Yu, Yao Shu:
Test-Time Policy Adaptation for Enhanced Multi-Turn Interactions with LLMs. CoRR abs/2509.23166 (2025) - [i25]Zikun Qu, Min Zhang, Mingze Kong, Xiang Li, Zhiwei Shang, Zhiyong Wang, Yikun Ban, Shuang Qiu, Yao Shu, Zhongxiang Dai:
T-POP: Test-Time Personalization with Online Preference Feedback. CoRR abs/2509.24696 (2025) - [i24]Pingchen Lu, Zhi Hong, Zhiwei Shang, Zhiyong Wang, Yikun Ban, Yao Shu, Min Zhang, Shuang Qiu, Zhongxiang Dai:
FedPOB: Sample-Efficient Federated Prompt Optimization via Bandits. CoRR abs/2509.24701 (2025) - [i23]Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai, Yao Shu:
Self-Reflective Generation at Test Time. CoRR abs/2510.02919 (2025) - [i22]Haotian Wu, Shufan Jiang, Mingyu Chen, Yiyang Feng, Hehai Lin, Heqing Zou, Yao Shu, Chengwei Qin:
FURINA: A Fully Customizable Role-Playing Benchmark via Scalable Multi-Agent Collaboration Pipeline. CoRR abs/2510.06800 (2025) - [i21]Hong Wang, Zhezheng Hao, Jian Luo, Chenxing Wei, Yao Shu, Lei Liu, Qiang Lin, Hande Dong, Jiawei Chen:
Scheduling Your LLM Reinforcement Learning with Reasoning Trees. CoRR abs/2510.24832 (2025) - 2024
- [j5]Hongchang Zhang
, Kang Yang, Heng Liu, Jiali Hu, Yao Shu, Juan Zeng:
Small-Scale Pedestrian Detection Using Fusion Network and Probabilistic Loss. IEEE Access 12: 42509-42520 (2024) - [c20]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Position Paper: Data-Centric AI in the Age of Large Language Models. EMNLP (Findings) 2024: 11895-11913 - [c19]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. ICLR 2024 - [c18]Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers. ICML 2024 - [c17]Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low:
Localized Zeroth-Order Prompt Optimization. NeurIPS 2024 - [c16]Yao Shu, Jiongfeng Fang, Ying He, Fei Richard Yu:
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. NeurIPS 2024 - [c15]Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. NeurIPS 2024 - [i20]Yao Shu, Jiongfeng Fang, Ying Tiffany He, Fei Richard Yu:
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. CoRR abs/2402.11427 (2024) - [i19]Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiangqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low:
Localized Zeroth-Order Prompt Optimization. CoRR abs/2403.02993 (2024) - [i18]Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low:
Robustifying and Boosting Training-Free Neural Architecture Search. CoRR abs/2403.07591 (2024) - [i17]Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. CoRR abs/2405.16122 (2024) - [i16]Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low:
Data-Centric AI in the Age of Large Language Models. CoRR abs/2406.14473 (2024) - [i15]Chenxing Wei, Yao Shu, Ying Tiffany He, Fei Richard Yu:
Flexora: Flexible Low Rank Adaptation for Large Language Models. CoRR abs/2408.10774 (2024) - [i14]Yao Shu, Wenyang Hu, See-Kiong Ng, Bryan Kian Hsiang Low, Fei Richard Yu:
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models. CoRR abs/2409.06277 (2024) - 2023
- [c14]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandits. ICLR 2023 - [c13]Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low:
Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation. ICLR 2023 - [c12]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. NeurIPS 2023 - [c11]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. NeurIPS 2023 - [i13]Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low:
Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. CoRR abs/2308.04077 (2023) - [i12]Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low:
Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers. CoRR abs/2310.02905 (2023) - [i11]Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Quantum Bayesian Optimization. CoRR abs/2310.05373 (2023) - [i10]Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low:
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. CoRR abs/2311.02715 (2023) - 2022
- [c10]Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low:
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. ICLR 2022 - [c9]Zhaoxuan Wu, Yao Shu, Bryan Kian Hsiang Low:
DAVINZ: Data Valuation using Deep Neural Networks at Initialization. ICML 2022: 24150-24176 - [c8]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. NeurIPS 2022 - [c7]Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low:
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. NeurIPS 2022 - [c6]Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low:
Neural ensemble search via Bayesian sampling. UAI 2022: 1803-1812 - [i9]Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low:
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. CoRR abs/2201.09785 (2022) - [i8]Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet:
Federated Neural Bandit. CoRR abs/2205.14309 (2022) - [i7]Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet:
Sample-Then-Optimize Batch Neural Thompson Sampling. CoRR abs/2210.06850 (2022) - 2021
- [c5]Shaofeng Cai, Yao Shu, Wei Wang:
Dynamic Routing Networks. WACV 2021: 3587-3596 - [i6]Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low:
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. CoRR abs/2109.00817 (2021) - [i5]Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low:
Going Beyond Neural Architecture Search with Sampling-based Neural Ensemble Search. CoRR abs/2109.02533 (2021) - 2020
- [j4]Yao Shu, Heng Zhang:
Multimodal information fusion based human movement recognition. Multim. Tools Appl. 79(7-8): 5043-5052 (2020) - [c4]Yao Shu, Wei Wang, Shaofeng Cai:
Understanding Architectures Learnt by Cell-based Neural Architecture Search. ICLR 2020 - [i4]Min Zhang, Yao Shu, Kun He:
Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization. CoRR abs/2010.08766 (2020)
2010 – 2019
- 2019
- [j3]Chenglei Zhang, Buyun Sheng, Xiyan Yin, Feiyu Zhao, Yao Shu:
Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing. J. Ambient Intell. Humaniz. Comput. 10(3): 1109-1128 (2019) - [j2]Buyun Sheng, Feiyu Zhao, Chenglei Zhang, Xiyan Yin, Yao Shu:
Parameterized representation and solution method of the lightweight 3D model virtual assembly constraint. J. Ambient Intell. Humaniz. Comput. 10(3): 1167-1187 (2019) - [j1]Heng Zhang, Jan D. Smeddinck, Rainer Malaka, Yao Shu, Chong Chen, Bo He, Zengjun Fu, Michael Lawo:
Wireless non-invasive motion tracking of functional behavior. Pervasive Mob. Comput. 54: 29-44 (2019) - [i3]Junzhe Zhang, Sai-Ho Yeung, Yao Shu, Bingsheng He, Wei Wang:
Efficient Memory Management for GPU-based Deep Learning Systems. CoRR abs/1903.06631 (2019) - [i2]Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi:
ISBNet: Instance-aware Selective Branching Network. CoRR abs/1905.04849 (2019) - 2018
- [c3]Chong Chen, Yao Shu, Kuang-I Shu, Heng Zhang:
WiTT: Modeling and the evaluation of table tennis actions based on WIFI signals. ICPR 2018: 3100-3107 - [c2]Yao Shu, Chong Chen, Kuang-I Shu, Heng Zhang:
Research on Human Motion Recognition Based on Wi-Fi and Inertial Sensor Signal Fusion. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2018: 496-504 - 2017
- [i1]Yao Shu, Man Zhu, Kun He, John E. Hopcroft, Pan Zhou:
Understanding Deep Representations through Random Weights. CoRR abs/1704.00330 (2017)
2000 – 2009
- 2005
- [c1]Jianxing Li, XinJun Mao, Yao Shu:
An OO-based Design Model of Software Agent. PDCAT 2005: 434-440
Coauthor Index
aka: Bryan Kian Hsiang Low
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