An OO-based Design Model of Software Agent. - Jianxing Li; XinJun Mao; Yao Shu (PDCAT, 2005)

Understanding Deep Representations through Random Weights. - Yao Shu; Man Zhu; Kun He 001; John E. Hopcroft; Pan Zhou 001 (CoRR, 2017)

WiTT: Modeling and the evaluation of table tennis actions based on WIFI signals. - Chong Chen; Yao Shu; Kuang-I Shu; Heng Zhang 012 (ICPR, 2018)

Research on Human Motion Recognition Based on Wi-Fi and Inertial Sensor Signal Fusion. - Yao Shu; Chong Chen; Kuang-I Shu; Heng Zhang 012 (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2018)

Efficient Memory Management for GPU-based Deep Learning Systems. - Junzhe Zhang 002; Sai-Ho Yeung; Yao Shu; Bingsheng He; Wei Wang 059 (CoRR, 2019)

ISBNet: Instance-aware Selective Branching Network. - Shaofeng Cai; Yao Shu; Wei Wang 059; Beng Chin Ooi (CoRR, 2019)

Parameterized representation and solution method of the lightweight 3D model virtual assembly constraint. - Buyun Sheng; Feiyu Zhao; Chenglei Zhang; Xiyan Yin; Yao Shu (J. Ambient Intell. Humaniz. Comput., 2019)

Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing. - Chenglei Zhang; Buyun Sheng; Xiyan Yin; Feiyu Zhao; Yao Shu (J. Ambient Intell. Humaniz. Comput., 2019)

Wireless non-invasive motion tracking of functional behavior. - Heng Zhang 012; Jan D. Smeddinck; Rainer Malaka; Yao Shu; Chong Chen; Bo He; Zengjun Fu; Michael Lawo (Pervasive Mob. Comput., 2019)

Understanding Architectures Learnt by Cell-based Neural Architecture Search. - Yao Shu; Wei Wang 059; Shaofeng Cai (ICLR, 2020)

Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization. - Min Zhang; Yao Shu; Kun He 001 (CoRR, 2020)

Multimodal information fusion based human movement recognition. - Yao Shu; Heng Zhang 012 (Multim. Tools Appl., 2020)

Dynamic Routing Networks. - Shaofeng Cai; Yao Shu; Wei Wang 059 (WACV, 2021)

Going Beyond Neural Architecture Search with Sampling-based Neural Ensemble Search. - Yao Shu; Yizhou Chen; Zhongxiang Dai; Bryan Kian Hsiang Low (CoRR, 2021)

NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. - Yao Shu; Shaofeng Cai; Zhongxiang Dai; Beng Chin Ooi; Bryan Kian Hsiang Low (ICLR, 2022)

DAVINZ: Data Valuation using Deep Neural Networks at Initialization. - Zhaoxuan Wu; Yao Shu; Bryan Kian Hsiang Low (ICML, 2022)

Sample-Then-Optimize Batch Neural Thompson Sampling. - Zhongxiang Dai; Yao Shu; Bryan Kian Hsiang Low; Patrick Jaillet (NeurIPS, 2022)

Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. - Yao Shu; Zhongxiang Dai; Zhaoxuan Wu; Bryan Kian Hsiang Low (NeurIPS, 2022)

Neural ensemble search via Bayesian sampling. - Yao Shu; Yizhou Chen; Zhongxiang Dai; Bryan Kian Hsiang Low (UAI, 2022)

Federated Neural Bandit. - Zhongxiang Dai; Yao Shu; Arun Verma; Flint Xiaofeng Fan; Bryan Kian Hsiang Low; Patrick Jaillet (CoRR, 2022)

Federated Neural Bandits. - Zhongxiang Dai; Yao Shu; Arun Verma; Flint Xiaofeng Fan; Bryan Kian Hsiang Low; Patrick Jaillet (ICLR, 2023)

Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation. - Yao Shu; Zhongxiang Dai; Weicong Sng; Arun Verma; Patrick Jaillet; Bryan Kian Hsiang Low (ICLR, 2023)

Quantum Bayesian Optimization. - Zhongxiang Dai; Gregory Kang Ruey Lau; Arun Verma; Yao Shu; Bryan Kian Hsiang Low; Patrick Jaillet (NeurIPS, 2023)

Exploiting Correlated Auxiliary Feedback in Parameterized Bandits. - Arun Verma; Zhongxiang Dai; Yao Shu; Bryan Kian Hsiang Low (NeurIPS, 2023)

Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. - Yao Shu; Xiaoqiang Lin; Zhongxiang Dai; Bryan Kian Hsiang Low (CoRR, 2023)

Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers. - Xiaoqiang Lin; Zhaoxuan Wu; Zhongxiang Dai; Wenyang Hu; Yao Shu; See-Kiong Ng; Patrick Jaillet; Bryan Kian Hsiang Low (CoRR, 2023)

Position Paper: Data-Centric AI in the Age of Large Language Models. - Xinyi Xu; Zhaoxuan Wu; Rui Qiao 006; Arun Verma; Yao Shu; Jingtan Wang 001; Xinyuan Niu 001; Zhenfeng He; Jiangwei Chen 001; Zijian Zhou; Gregory Kang Ruey Lau; Hieu Dao; et al. (EMNLP (Findings), 2024)

Robustifying and Boosting Training-Free Neural Architecture Search. - Zhenfeng He; Yao Shu; Zhongxiang Dai; Bryan Kian Hsiang Low (ICLR, 2024)

Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers. - Xiaoqiang Lin; Zhaoxuan Wu; Zhongxiang Dai; Wenyang Hu; Yao Shu; See-Kiong Ng; Patrick Jaillet; Bryan Kian Hsiang Low (ICML, 2024)

Localized Zeroth-Order Prompt Optimization. - Wenyang Hu; Yao Shu; Zongmin Yu; Zhaoxuan Wu; Xiaoqiang Lin; Zhongxiang Dai; See-Kiong Ng; Bryan Kian Hsiang Low (NeurIPS, 2024)

OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. - Yao Shu; Jiongfeng Fang; Ying He 006; Fei Richard Yu (NeurIPS, 2024)

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. - Zhaoxuan Wu; Xiaoqiang Lin; Zhongxiang Dai; Wenyang Hu; Yao Shu; See-Kiong Ng; Patrick Jaillet; Bryan Kian Hsiang Low (NeurIPS, 2024)

Small-Scale Pedestrian Detection Using Fusion Network and Probabilistic Loss. - Hongchang Zhang; Kang Yang; Heng Liu; Jiali Hu; Yao Shu; Juan Zeng (IEEE Access, 2024)

OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations. - Yao Shu; Jiongfeng Fang; Ying Tiffany He; Fei Richard Yu (CoRR, 2024)

Localized Zeroth-Order Prompt Optimization. - Wenyang Hu; Yao Shu; Zongmin Yu; Zhaoxuan Wu; Xiangqiang Lin; Zhongxiang Dai; See-Kiong Ng; Bryan Kian Hsiang Low (CoRR, 2024)

Data-Centric AI in the Age of Large Language Models. - Xinyi Xu; Zhaoxuan Wu; Rui Qiao 006; Arun Verma; Yao Shu; Jingtan Wang 001; Xinyuan Niu 001; Zhenfeng He; Jiangwei Chen 001; Zijian Zhou; Gregory Kang Ruey Lau; Hieu Dao; et al. (CoRR, 2024)

Flexora: Flexible Low Rank Adaptation for Large Language Models. - Chenxing Wei; Yao Shu; Ying Tiffany He; Fei Richard Yu (CoRR, 2024)

Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models. - Yao Shu; Wenyang Hu; See-Kiong Ng; Bryan Kian Hsiang Low; Fei Richard Yu (CoRR, 2024)

FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation. - Yunwei Bai; Ying Kiat Tan; Shiming Chen 002; Yao Shu; Tsuhan Chen (AAAI, 2025)

Flexora: Flexible Low-Rank Adaptation for Large Language Models. - Chenxing Wei; Yao Shu; Ying Tiffany He; Fei Yu (ACL (1), 2025)

Characterizing Logs in Vulnerability Reports: In-Depth Analysis and Security Implications. - Yao Shu; Lianyu Zheng; Jinfu Chen 006; Jifeng Xuan (SANER, 2025)

Meta-Prompt Optimization for LLM-Based Sequential Decision Making. - Mingze Kong; Zhiyong Wang; Yao Shu; Zhongxiang Dai (CoRR, 2025)

Refining Adaptive Zeroth-Order Optimization at Ease. - Yao Shu; Qixin Zhang 001; Kun He 001; Zhongxiang Dai (CoRR, 2025)

PAFT: Prompt-Agnostic Fine-Tuning. - Chenxing Wei; Yao Shu; Mingwen Ou; Ying Tiffany He; Fei Richard Yu (CoRR, 2025)

On Path to Multimodal Historical Reasoning: HistBench and HistAgent. - Jiahao Qiu; Fulian Xiao; Yimin Wang; Yuchen Mao; Yijia Chen; Xinzhe Juan; Siran Wang; Xuan Qi; Tongcheng Zhang; Zixin Yao; Jiacheng Guo; Yifu Lu; et al. (CoRR, 2025)

Zeroth-Order Optimization is Secretly Single-Step Policy Optimization. - Junbin Qiu; Zhengpeng Xie; Xiangda Yan; Yongjie Yang 010; Yao Shu (CoRR, 2025)

ReDit: Reward Dithering for Improved LLM Policy Optimization. - Chenxing Wei; Jiarui Yu; Ying Tiffany He; Hande Dong; Yao Shu; Fei Yu (CoRR, 2025)

Thinking with Nothinking Calibration: A New In-Context Learning Paradigm in Reasoning Large Language Models. - Haotian Wu; Bo Xu; Yao Shu; Menglin Yang 005; Chengwei Qin (CoRR, 2025)