The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design. - Ruoyu Cheng; Xianglong Lyu; Yang Li 197; Junjie Ye; Jianye Hao; Junchi Yan (NeurIPS, 2022)

Improving Generative Adversarial Networks via Adversarial Learning in Latent Space. - Yang Li 197; Yichuan Mo; Liangliang Shi; Junchi Yan (NeurIPS, 2022)

IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse. - Yang Li 197; Liangliang Shi; Junchi Yan (IJCAI, 2023)

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline. - Yang Li 197; Xinyan Chen; Wenxuan Guo; Xijun Li; Wanqian Luo; Junhua Huang; Hui-Ling Zhen; Mingxuan Yuan; Junchi Yan (KDD, 2023)

From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization. - Yang Li 197; Jinpei Guo; Runzhong Wang; Junchi Yan (NeurIPS, 2023)

Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems. - Haoyu Geng; Hang Ruan; Runzhong Wang; Yang Li 197; Yang Wang; Lei Chen 031; Junchi Yan (CoRR, 2023)

MixSATGEN: Learning Graph Mixing for SAT Instance Generation. - Xinyan Chen; Yang Li 197; Runzhong Wang; Junchi Yan (ICLR, 2024)

ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation. - Ziao Guo; Yang Li 197; Chang Liu 021; Wenli Ouyang; Junchi Yan (ICML, 2024)

Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime. - Haoyu Geng; Hang Ruan; Runzhong Wang; Yang Li 197; Yang Wang; Lei Chen 031; Junchi Yan (NeurIPS, 2024)

Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization. - Yang Li 197; Jinpei Guo; Runzhong Wang; Hongyuan Zha; Junchi Yan (NeurIPS, 2024)

Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation. - Xinhao Zheng; Yang Li 197; Cunxin Fan; Huaijin Wu; Xinhao Song; Junchi Yan (NeurIPS, 2024)

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. - Xijun Li; Fangzhou Zhu; Hui-Ling Zhen; Weilin Luo; Meng Lu; Yimin Huang; Zhenan Fan; Zirui Zhou; Yufei Kuang; Zhihai Wang; Zijie Geng; Yang Li 197; et al. (CoRR, 2024)

Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks. - Runzhong Wang; Yang Li 197; Junchi Yan; Xiaokang Yang 001 (CoRR, 2024)

Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search. - Yang Li 197; Jiale Ma; Wenzheng Pan; Runzhong Wang; Haoyu Geng; Nianzu Yang; Junchi Yan (ICLR, 2025)

UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP. - Wenzheng Pan; Hao Xiong 003; Jiale Ma; Wentao Zhao; Yang Li 197; Junchi Yan (ICLR, 2025)

Rethinking Video Tokenization: A Conditioned Diffusion-based Approach. - Nianzu Yang; Pandeng Li; Liming Zhao; Yang Li 197; Chen-Wei Xie; Yehui Tang; Xudong Lu; Zhihang Liu; Yun Zheng; Yu Liu 015; Junchi Yan (CoRR, 2025)