Yao Shu

According to our database, Yao Shu authored at least 77 papers between 2005 and 2026.

Collaborative distances:

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

2026

DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization.

Jian Mu, Tianyi Lin, Chengwei Qin, Zhongxiang Dai, Yao Shu

CoRR, May, 2026

Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens.

Junbin Qiu, Zhaowei Hong, Renzhe Xu, Yao Shu

CoRR, May, 2026

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning.

Ziye Chen, Hongbin Lin, Chenyu Zhang, Xiangda Yan, Yongjie Yang, Yao Shu

CoRR, May, 2026

Compander-Aligned Query Geometry for Quantized Zeroth-Order Optimization.

Yao Shu, Zilin Zhu

CoRR, May, 2026

Why Zeroth-Order Adaptation May Forget Less: A Randomized Shaping Theory.

Yao Shu, Jian Mu, Zhongxiang Dai

CoRR, May, 2026

Reference-Sampled Boltzmann Projection for KL-Regularized RLVR: Target-Matched Weighted SFT, Finite One-Shot Gaps, and Policy Mirror Descent.

Yao Shu, Chenxing Wei, Hongbin Lin, Shuang Qiu, Hui Xiong

CoRR, May, 2026

Can We Change the Stroke Size for Easier Diffusion?

Yunwei Bai, Ying Kiat Tan, Yao Shu, Tsuhan Chen

CoRR, March, 2026

Multinoulli Extension: A Lossless Continuous Relaxation for Partition-Constrained Subset Selection.

Qixin Zhang, Wei Huang, Yan Sun, Yao Shu, Yi Yu, Dacheng Tao

CoRR, March, 2026

Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting.

Zhongjian Qiao, Jiafei Lyu, Boxiang Lyu, Yao Shu, Siyang Gao, Shuang Qiu

CoRR, March, 2026

ACE-Merging: Data-Free Model Merging with Adaptive Covariance Estimation.

Bo Xu, Haotian Wu, Hehai Lin, Weiquan Huang, Beier Zhu, Yao Shu, Chengwei Qin

CoRR, March, 2026

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks.

Zhi Hong, Qian Zhang, Jiahang Sun, Zhiwei Shang, Mingze Kong, Xiangyi Wang, Yao Shu, Zhongxiang Dai

CoRR, March, 2026

LFPO: Likelihood-Free Policy Optimization for Masked Diffusion Models.

Chenxing Wei, Jiazhen Kang, Hong Wang, Jianqing Zhang, Hao Jiang, Xiaolong Xu, Ningyuan Sun, Ying He, F. Richard Yu, Yao Shu, Bo Jiang

CoRR, March, 2026

Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation.

Chenxing Wei, Hong Wang, Ying He, Zhongxiang Dai, Bo Jiang, F. Richard Yu, Yao Shu

CoRR, March, 2026

Training Multi-Turn Search Agent via Contrastive Dynamic Branch Sampling.

Yubao Zhao, Weiquan Huang, Sudong Wang, Ruochen Zhao, Chen Chen, Yao Shu, Chengwei Qin

CoRR, February, 2026

1S-DAug: One-Shot Data Augmentation for Robust Few-Shot Generalization.

Yunwei Bai, Ying Kiat Tan, Yao Shu, Tsuhan Chen

CoRR, February, 2026

Controllable Concept Bottleneck Models.

Hongbin Lin, Chenyang Ren, Juangui Xu, Zhengyu Hu, Cheng-Long Wang, Yao Shu, Hui Xiong, Jingfeng Zhang, Di Wang, Lijie Hu

CoRR, January, 2026

Optimization and Robustness-Informed Membership Inference Attacks for LLMs.

Zichen Song, Qixin Zhang, Ming Li, Yao Shu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Scheduling Your LLM Reinforcement Learning with Reasoning Trees.

Hong Wang, Zhezheng Hao, Jian Luo, Chenxing Wei, Yao Shu, Lei Liu, Qiang Lin, Hande Dong, Jiawei Chen

CoRR, October, 2025

FURINA: A Fully Customizable Role-Playing Benchmark via Scalable Multi-Agent Collaboration Pipeline.

Haotian Wu, Shufan Jiang, Mingyu Chen, Yiyang Feng, Hehai Lin, Heqing Zou, Yao Shu, Chengwei Qin

CoRR, October, 2025

Self-Reflective Generation at Test Time.

Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai, Yao Shu

CoRR, October, 2025

FedPOB: Sample-Efficient Federated Prompt Optimization via Bandits.

Pingchen Lu, Zhi Hong, Zhiwei Shang, Zhiyong Wang, Yikun Ban, Yao Shu, Min Zhang, Shuang Qiu, Zhongxiang Dai

CoRR, September, 2025

T-POP: Test-Time Personalization with Online Preference Feedback.

Zikun Qu, Min Zhang, Mingze Kong, Xiang Li, Zhiwei Shang, Zhiyong Wang, Yikun Ban, Shuang Qiu, Yao Shu, Zhongxiang Dai

CoRR, September, 2025

Test-Time Policy Adaptation for Enhanced Multi-Turn Interactions with LLMs.

Chenxing Wei, Hong Wang, Ying He, Fei Yu, Yao Shu

CoRR, September, 2025

RIMO: An Easy-to-Evaluate, Hard-to-Solve Olympiad Benchmark for Advanced Mathematical Reasoning.

Ziye Chen, Chengwei Qin, Yao Shu

CoRR, September, 2025

Implicit Reasoning in Large Language Models: A Comprehensive Survey.

Jindong Li, Yali Fu, Li Fan, Jiahong Liu, Yao Shu, Chengwei Qin, Menglin Yang, Irwin King, Rex Ying

CoRR, September, 2025

Thinking with Nothinking Calibration: A New In-Context Learning Paradigm in Reasoning Large Language Models.

Haotian Wu, Bo Xu, Yao Shu, Menglin Yang, Chengwei Qin

CoRR, August, 2025

ReDit: Reward Dithering for Improved LLM Policy Optimization.

Chenxing Wei, Jiarui Yu, Ying Tiffany He, Hande Dong, Yao Shu, Fei Yu

CoRR, June, 2025

Zeroth-Order Optimization is Secretly Single-Step Policy Optimization.

Junbin Qiu, Zhengpeng Xie, Xiangda Yan, Yongjie Yang, Yao Shu

CoRR, June, 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, 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

CoRR, May, 2025

PAFT: Prompt-Agnostic Fine-Tuning.

Chenxing Wei, Yao Shu, Mingwen Ou, Ying Tiffany He, Fei Richard Yu

CoRR, February, 2025

Meta-Prompt Optimization for LLM-Based Sequential Decision Making.

Mingze Kong, Zhiyong Wang, Yao Shu, Zhongxiang Dai

CoRR, February, 2025

Characterizing Logs in Vulnerability Reports: In-Depth Analysis and Security Implications.

Yao Shu, Lianyu Zheng, Jinfu Chen, Jifeng Xuan

Proceedings of the IEEE International Conference on Software Analysis, 2025

Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives.

Qixin Zhang, Yan Sun, Can Jin, Xikun Zhang, Yao Shu, Puning Zhao, Li Shen, Dacheng Tao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

WMarkGPT: Watermarked Image Understanding via Multimodal Large Language Models.

Songbai Tan, Xuerui Qiu, Yao Shu, Gang Xu, Linrui Xu, Xiangyu Xu, Huiping Zhuang, Ming Li, Fei Richard Yu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Refining Adaptive Zeroth-Order Optimization at Ease.

Yao Shu, Qixin Zhang, Kun He, Zhongxiang Dai

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Multinoulli Extension: A Lossless Yet Effective Probabilistic Framework for Subset Selection over Partition Constraints.

Qixin Zhang, Wei Huang, Can Jin, Puning Zhao, Yao Shu, Li Shen, Dacheng Tao

Proceedings of the Forty-second International Conference on Machine Learning, 2025

PAFT: Prompt-Agnostic Fine-Tuning.

Chenxing Wei, Mingwen Ou, Ying He, Yao Shu, Fei Yu

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Flexora: Flexible Low-Rank Adaptation for Large Language Models.

Chenxing Wei, Yao Shu, Ying Tiffany He, Fei Yu

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation.

Yunwei Bai, Ying Kiat Tan, Shiming Chen, Yao Shu, Tsuhan Chen

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Flexora: Flexible Low Rank Adaptation for Large Language Models.

Chenxing Wei, Yao Shu, Ying Tiffany He, Fei Richard Yu

CoRR, 2024

Data-Centric AI in the Age of Large Language Models.

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

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

OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations.

Yao Shu, Jiongfeng Fang, Ying Tiffany He, Fei Richard Yu

CoRR, 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

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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations.

Yao Shu, Jiongfeng Fang, Ying He, Fei Richard Yu

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Robustifying and Boosting Training-Free Neural Architecture Search.

Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Position Paper: Data-Centric AI in the Age of Large Language Models.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

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

Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients.

Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low

CoRR, 2023

Exploiting Correlated Auxiliary Feedback in Parameterized Bandits.

Arun Verma, Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quantum Bayesian Optimization.

Zhongxiang Dai, Gregory Kang Ruey Lau, Arun Verma, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation.

Yao Shu, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet, Bryan Kian Hsiang Low

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Federated Neural Bandits.

Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Federated Neural Bandit.

Zhongxiang Dai, Yao Shu, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low, Patrick Jaillet

CoRR, 2022

Neural ensemble search via Bayesian sampling.

Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search.

Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample-Then-Optimize Batch Neural Thompson Sampling.

Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DAVINZ: Data Valuation using Deep Neural Networks at Initialization.

Zhaoxuan Wu, Yao Shu, Bryan Kian Hsiang Low

Proceedings of the International Conference on Machine Learning, 2022

NASI: Label- and Data-agnostic Neural Architecture Search at Initialization.

Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Going Beyond Neural Architecture Search with Sampling-based Neural Ensemble Search.

Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low

CoRR, 2021

Dynamic Routing Networks.

Shaofeng Cai, Yao Shu, Wei Wang

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020

Multimodal information fusion based human movement recognition.

Yao Shu, Heng Zhang

Multim. Tools Appl., 2020

Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization.

Min Zhang, Yao Shu, Kun He

CoRR, 2020

Understanding Architectures Learnt by Cell-based Neural Architecture Search.

Yao Shu, Wei Wang, Shaofeng Cai

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Wireless non-invasive motion tracking of functional behavior.

Heng Zhang, Jan D. Smeddinck, Rainer Malaka, Yao Shu, Chong Chen, Bo He, Zengjun Fu, Michael Lawo

Pervasive Mob. 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

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

ISBNet: Instance-aware Selective Branching Network.

Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi

CoRR, 2019

Efficient Memory Management for GPU-based Deep Learning Systems.

Junzhe Zhang, Sai-Ho Yeung, Yao Shu, Bingsheng He, Wei Wang

CoRR, 2019

2018

Research on Human Motion Recognition Based on Wi-Fi and Inertial Sensor Signal Fusion.

Yao Shu, Chong Chen, Kuang-I Shu, Heng Zhang

Proceedings of the 2018 IEEE SmartWorld, 2018

WiTT: Modeling and the evaluation of table tennis actions based on WIFI signals.

Chong Chen, Yao Shu, Kuang-I Shu, Heng Zhang

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

Understanding Deep Representations through Random Weights.

Yao Shu, Man Zhu, Kun He, John E. Hopcroft, Pan Zhou

CoRR, 2017

2005

An OO-based Design Model of Software Agent.

Jianxing Li, XinJun Mao, Yao Shu

Proceedings of the Sixth International Conference on Parallel and Distributed Computing, 2005