Shanda Li - RankMe

31 papers A* 8A 2Journal 21

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization. AAAI Weiwei Sun, Shengyu Feng, Shanda Li, Yiming Yang
2026	J	`jnl`	CodePDE: An Inference Framework for LLM-driven PDE Solver Generation. Trans. Mach. Learn. Res. Shanda Li, Tanya Marwah, Junhong Shen, Weiwei Sun, Andrej Risteski, Yiming Yang, Ameet Talwalkar
2026	J	`jnl`	Learn Hard Problems During RL with Reference Guided Fine-tuning. CoRR Yangzhen Wu, Shanda Li, Zixin Wen, Xin Zhou, Ameet Talwalkar, Yiming Yang, Wenhao Huang, Tianle Cai
2026	J	`jnl`	Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces. CoRR 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
2025	J	`jnl`	A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial Optimization. CoRR Shengyu Feng, Weiwei Sun, Shanda Li, Ameet Talwalkar, Yiming Yang
2025	J	`jnl`	CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization. CoRR Weiwei Sun, Shengyu Feng, Shanda Li, Yiming Yang
2025	J	`jnl`	CodePDE: An Inference Framework for LLM-driven PDE Solver Generation. CoRR Shanda Li, Tanya Marwah, Junhong Shen, Weiwei Sun, Andrej Risteski, Yiming Yang, Ameet Talwalkar
2025	A*	`conf`	Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving. ICLR Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang
2025	A*	`conf`	Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators. ICML Shanda Li, Shinjae Yoo, Yiming Yang
2025	J	`jnl`	Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators. CoRR Shanda Li, Shinjae Yoo, Yiming Yang
2025	J	`jnl`	Sample Complexity and Representation Ability of Test-time Scaling Paradigms. CoRR Baihe Huang, Shanda Li, Tianhao Wu, Yiming Yang, Ameet Talwalkar, Kannan Ramchandran, Michael I. Jordan, Jiantao Jiao
2025	J	`jnl`	Scaling Latent Reasoning via Looped Language Models. CoRR 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
2025	A*	`conf`	TFG-Flow: Training-free Guidance in Multimodal Generative Flow. ICLR Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma
2025	J	`jnl`	TFG-Flow: Training-free Guidance in Multimodal Generative Flow. CoRR Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma
2025	J	`jnl`	Towards Community-Driven Agents for Machine Learning Engineering. CoRR Sijie Li, Weiwei Sun, Shanda Li, Ameet Talwalkar, Yiming Yang
2024	J	`jnl`	A visual detection algorithm for autonomous driving road environment perception. Eng. Appl. Artif. Intell. Peichao Cong, Hao Feng, Shanda Li, Tianheng Li, Yutao Xu, Xin Zhang
2024	J	`jnl`	An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models. CoRR Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang
2024	A*	`conf`	Functional Interpolation for Relative Positions improves Long Context Transformers. ICLR Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
2024	J	`jnl`	KM-Mask RCNN: A Lightweight Instance Segmentation Algorithm for Strawberries With Multiple Growth Cycles. IEEE Access Peichao Cong, Yutao Xu, Tianheng Li, Shanda Li, Hao Feng, Xin Zhang
2024	A	`conf`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2023	J	`jnl`	Functional Interpolation for Relative Positions Improves Long Context Transformers. CoRR Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
2023	A	`conf`	Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
2023	J	`jnl`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2022	A*	`conf`	Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? NeurIPS Chuwei Wang, Shanda Li, Di He, Liwei Wang
2022	J	`jnl`	Is L CoRR Chuwei Wang, Shanda Li, Di He, Liwei Wang
2022	J	`jnl`	Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
2022	A*	`conf`	Your Transformer May Not be as Powerful as You Expect. NeurIPS Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
2022	J	`jnl`	Your Transformer May Not be as Powerful as You Expect. CoRR Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
2021	J	`jnl`	Can Vision Transformers Perform Convolution? CoRR Shanda Li, Xiangning Chen, Di He, Cho-Jui Hsieh
2021	A*	`conf`	Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
2021	J	`jnl`	Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu