Lin, Junhong

19 publications

ICLR 2026 $AutoDrive\text{-}p^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning Yuqi Ye, Zijian Zhang, Junhong Lin, Shangkun Sun, Changhao Peng, Wei Gao

ICLR 2026 HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs Xinyue Zeng, Junhong Lin, Yujun Yan, Feng Guo, Liang Shi, Jun Wu, Dawei Zhou

ICLR 2026 Plan and Budget: Effective and Efficient Test-Time Scaling on Reasoning Large Language Models Junhong Lin, Xinyue Zeng, Jie Zhu, Song Wang, Julian Shun, Jun Wu, Dawei Zhou

ICLR 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, E. Kelly Buchanan, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, Marianna Nezhurina, 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 Kwesi 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, Christopher Michael Rytting, Ryan Marten, Yixin Wang, Jenia Jitsev, Alex Dimakis, Andy Konwinski, Ludwig Schmidt

NeurIPS 2025 HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations Shuaicheng Zhang, Haohui Wang, Junhong Lin, Xiaojie Guo, Yada Zhu, Si Zhang, Dongqi Fu, Dawei Zhou

ICML 2025 LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou

ICLR 2025 Reasoning of Large Language Models over Knowledge Graphs with Super-Relations Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu

NeurIPS 2025 Theoretical Investigation of Adafactor for Non-Convex Smooth Optimization Yusu Hong, Junhong Lin

NeurIPS 2024 On Convergence of Adam for Stochastic Optimization Under Relaxed Assumptions Yusu Hong, Junhong Lin

UAI 2024 Revisiting Convergence of AdaGrad with Relaxed Assumptions Yusu Hong, Junhong Lin

JMLR 2020 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections Junhong Lin, Volkan Cevher

JMLR 2020 Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms Junhong Lin, Volkan Cevher

ICML 2018 Optimal Distributed Learning with Multi-Pass Stochastic Gradient Methods Junhong Lin, Volkan Cevher

ICML 2018 Optimal Rates of Sketched-Regularized Algorithms for Least-Squares Regression over Hilbert Spaces Junhong Lin, Volkan Cevher

JMLR 2017 Optimal Rates for Multi-Pass Stochastic Gradient Methods Junhong Lin, Lorenzo Rosasco

ICML 2016 Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco

JMLR 2016 Iterative Regularization for Learning with Convex Loss Functions Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou

NeurIPS 2016 Optimal Learning for Multi-Pass Stochastic Gradient Methods Junhong Lin, Lorenzo Rosasco

JMLR 2015 Learning Theory of Randomized Kaczmarz Algorithm Junhong Lin, Ding-Xuan Zhou