Shanda Li

According to our database, Shanda Li authored at least 23 papers between 2021 and 2026.

Collaborative distances:

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

2026

Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection.

Sijie Li, Shanda Li, Haowei Lin, Weiwei Sun, Ameet Talwalkar, Yiming Yang

CoRR, April, 2026

Learn Hard Problems During RL with Reference Guided Fine-tuning.

Yangzhen Wu, Shanda Li, Zixin Wen, Xin Zhou, Ameet Talwalkar, Yiming Yang, Wenhao Huang, Tianle Cai

CoRR, March, 2026

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces.

Mike A. Merrill, Alexander Glenn Shaw, Nicholas Carlini, Boxuan Li, Harsh Raj, Ivan Bercovich, Lin Shi, Jeong Yeon Shin, Thomas Walshe, Estefany Kelly Buchanan, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, Marianna Nezhurina, Jenia Jitsev, Di Lu, Orfeas Menis-Mastromichalakis, Zhiwei Xu, Zizhao Chen, Yue Liu, Robert Zhang, Leon Liangyu Chen, Anurag Kashyap, Jan-Lucas Uslu, Jeffrey Li, Jianbo Wu, Minghao Yan, Song Bian, Vedang Sharma, Ke Sun, Steven Dillmann, Akshay Anand, Andrew Lanpouthakoun, Bardia Koopah, Changran Hu, Etash Kumar Guha, Gabriel H. S. Dreiman, Jiacheng Zhu, Karl Krauth, Li Zhong, Niklas Muennighoff, Robert Amanfu, Shangyin Tan, Shreyas Pimpalgaonkar, Tushar Aggarwal, Xiangning Lin, Xin Lan, Xuandong Zhao, Yiqing Liang, Yuanli Wang, Zilong Wang, Changzhi Zhou, David Heineman, Hange Liu, Harsh Trivedi, John Yang, Junhong Lin, Manish Shetty, Michael Yang, Nabil Omi, Negin Raoof, Shanda Li, Terry Yue Zhuo, Wuwei Lin, Yiwei Dai, Yuxin Wang, Wenhao Chai, Shang Zhou, Dariush Wahdany, Ziyu She, Jiaming Hu, Zhikang Dong, Yuxuan Zhu, Sasha Cui, Ahson Saiyed, Arinbjörn Kolbeinsson, Jesse Hu, Christopher Michael Rytting, Ryan Marten, Yixin Wang, Alex Dimakis, Andy Konwinski, Ludwig Schmidt

CoRR, January, 2026

CodePDE: An Inference Framework for LLM-driven PDE Solver Generation.

Shanda Li, Tanya Marwah, Junhong Shen, Weiwei Sun, Andrej Risteski, Yiming Yang, Ameet Talwalkar

Trans. Mach. Learn. Res., 2026

CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization.

Weiwei Sun, Shengyu Feng, Shanda Li, Yiming Yang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Scaling Latent Reasoning via Looped Language Models.

Rui-Jie Zhu, Zixuan Wang, Kai Hua, Tianyu Zhang, Ziniu Li, Haoran Que, Boyi Wei, Zixin Wen, Fan Yin, He Xing, Lu Li, Jiajun Shi, Kaijing Ma, Shanda Li, Taylor Kergan, Andrew Smith, Xingwei Qu, Mude Hui, Bohong Wu, Qiyang Min, Hongzhi Huang, Xun Zhou, Wei Ye, Jiaheng Liu, Jian Yang, Yunfeng Shi, Chenghua Lin, Enduo Zhao, Tianle Cai, Ge Zhang, Wenhao Huang, Yoshua Bengio, Jason Eshraghian

CoRR, October, 2025

Towards Community-Driven Agents for Machine Learning Engineering.

Sijie Li, Weiwei Sun, Shanda Li, Ameet Talwalkar, Yiming Yang

CoRR, June, 2025

Sample Complexity and Representation Ability of Test-time Scaling Paradigms.

Baihe Huang, Shanda Li, Tianhao Wu, Yiming Yang, Ameet Talwalkar, Kannan Ramchandran, Michael I. Jordan, Jiantao Jiao

CoRR, June, 2025

A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial Optimization.

Shengyu Feng, Weiwei Sun, Shanda Li, Ameet Talwalkar, Yiming Yang

CoRR, May, 2025

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators.

Shanda Li, Shinjae Yoo, Yiming Yang

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

TFG-Flow: Training-free Guidance in Multimodal Generative Flow.

Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models.

Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang

CoRR, 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

IEEE Access, 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, Sanjiv Kumar, Srinadh Bhojanapalli

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers.

Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Learning Physics-Informed Neural Networks without Stacked Back-propagation.

Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Is L² Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network?

Chuwei Wang, Shanda Li, Di He, Liwei Wang

CoRR, 2022

Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?

Chuwei Wang, Shanda Li, Di He, Liwei Wang

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

Your Transformer May Not be as Powerful as You Expect.

Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

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

2021

Can Vision Transformers Perform Convolution?

Shanda Li, Xiangning Chen, Di He, Cho-Jui Hsieh

CoRR, 2021

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding.

Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021