Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. - Shengjie Luo; Shanda Li; Tianle Cai; Di He 001; Dinglan Peng; Shuxin Zheng; Guolin Ke; Liwei Wang 001; Tie-Yan Liu (NeurIPS, 2021)

Can Vision Transformers Perform Convolution? - Shanda Li; Xiangning Chen; Di He 001; Cho-Jui Hsieh (CoRR, 2021)

Your Transformer May Not be as Powerful as You Expect. - Shengjie Luo; Shanda Li; Shuxin Zheng; Tie-Yan Liu; Liwei Wang 001; Di He 001 (NeurIPS, 2022)

Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? - Chuwei Wang; Shanda Li; Di He 001; Liwei Wang 001 (NeurIPS, 2022)

Is L2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network? - Chuwei Wang; Shanda Li; Di He 001; Liwei Wang 001 (CoRR, 2022)

Learning Physics-Informed Neural Networks without Stacked Back-propagation. - Di He 001; Shanda Li; Wenlei Shi; Xiaotian Gao; Jia Zhang 004; Jiang Bian 002; Liwei Wang 001; Tie-Yan Liu (AISTATS, 2023)

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. - Krzysztof Choromanski; Shanda Li; Valerii Likhosherstov; Kumar Avinava Dubey; Shengjie Luo; Di He 001; Yiming Yang; Tamás Sarlós; Thomas Weingarten; Adrian Weller (AISTATS, 2024)

Functional Interpolation for Relative Positions improves Long Context Transformers. - Shanda Li; Chong You; Guru Guruganesh; Joshua Ainslie; Santiago Ontañón; Manzil Zaheer; Sumit Sanghai; Yiming Yang 002; Sanjiv Kumar; Srinadh Bhojanapalli (ICLR, 2024)

KM-Mask RCNN: A Lightweight Instance Segmentation Algorithm for Strawberries With Multiple Growth Cycles. - Peichao Cong; Yutao Xu; Tianheng Li; Shanda Li; Hao Feng; Xin Zhang 109 (IEEE Access, 2024)

An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models. - Yangzhen Wu; Zhiqing Sun; Shanda Li; Sean Welleck; Yiming Yang 002 (CoRR, 2024)

A visual detection algorithm for autonomous driving road environment perception. - Peichao Cong; Hao Feng; Shanda Li; Tianheng Li; Yutao Xu; Xin Zhang (Eng. Appl. Artif. Intell., 2024)

TFG-Flow: Training-free Guidance in Multimodal Generative Flow. - Haowei Lin; Shanda Li; Haotian Ye; Yiming Yang; Stefano Ermon; Yitao Liang; Jianzhu Ma (ICLR, 2025)

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving. - Yangzhen Wu; Zhiqing Sun; Shanda Li; Sean Welleck; Yiming Yang 002 (ICLR, 2025)

CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization. - Weiwei Sun 001; Shengyu Feng; Shanda Li; Yiming Yang 002 (CoRR, 2025)

CodePDE: An Inference Framework for LLM-driven PDE Solver Generation. - Shanda Li; Tanya Marwah; Junhong Shen; Weiwei Sun 001; Andrej Risteski; Yiming Yang 002; Ameet Talwalkar (CoRR, 2025)

A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial Optimization. - Shengyu Feng; Weiwei Sun 001; Shanda Li; Ameet Talwalkar; Yiming Yang 002 (CoRR, 2025)

Sample Complexity and Representation Ability of Test-time Scaling Paradigms. - Baihe Huang; Shanda Li; Tianhao Wu 002; Yiming Yang 002; Ameet Talwalkar; Kannan Ramchandran; Michael I. Jordan; Jiantao Jiao (CoRR, 2025)

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators. - Shanda Li; Shinjae Yoo; Yiming Yang 002 (CoRR, 2025)

Towards Community-Driven Agents for Machine Learning Engineering. - Sijie Li; Weiwei Sun 001; Shanda Li; Ameet Talwalkar; Yiming Yang 002 (CoRR, 2025)

Scaling Latent Reasoning via Looped Language Models. - Rui-Jie Zhu 003; Zixuan Wang; Kai Hua; Tianyu Zhang; Ziniu Li; Haoran Que; Boyi Wei; Zixin Wen; Fan Yin; He Xing; Lu Li; Jiajun Shi; et al. (CoRR, 2025)