Dai, Hanjun

65 publications

TMLR 2026 Beyond Expectations: Learning with Stochastic Dominance Made Practical Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai

NeurIPS 2025 AmorLIP: Efficient Language-Image Pretraining via Amortization Haotian Sun, Yitong Li, Yuchen Zhuang, Niao He, Hanjun Dai, Bo Dai

AISTATS 2025 Faster WIND: Accelerating Iterative Best-of-$n$ Distillation for LLM Alignment Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai

NeurIPS 2025 Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs ChangHao Li, Yuchen Zhuang, Rushi Qiang, Haotian Sun, Hanjun Dai, Chao Zhang, Bo Dai

ICLR 2025 Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai

ICML 2024 Preference Optimization for Molecule Synthesis with Conditional Residual Energy-Based Models Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu

TMLR 2024 SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL Ruoxi Sun, Sercan O Arik, Alexandre Muzio, Lesly Miculicich, Satya Kesav Gundabathula, Pengcheng Yin, Hanjun Dai, Hootan Nakhost, Rajarishi Sinha, Zifeng Wang, Tomas Pfister

NeurIPS 2024 UQE: A Query Engine for Unstructured Databases Hanjun Dai, Bethany Yixin Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans

ICLR 2023 Any-Scale Balanced Samplers for Discrete Space Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai

NeurIPS 2023 DISCS: A Benchmark for Discrete Sampling Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai

ICMLW 2023 DISCS: A Benchmark for Discrete Sampling Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Sussman Grathwohl, Dale Schuurmans, Hanjun Dai

AISTATS 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans

ICML 2023 Gradient-Free Structured Pruning with Unlabeled Data Azade Nova, Hanjun Dai, Dale Schuurmans

NeurIPS 2023 LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles A. Sutton

NeurIPS 2023 Learning Universal Policies via Text-Guided Video Generation Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel

AISTATS 2023 Learning to Optimize with Stochastic Dominance Constraints Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai

NeurIPS 2023 Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan

ICML 2023 Revisiting Sampling for Combinatorial Optimization Haoran Sun, Katayoon Goshvadi, Azade Nova, Dale Schuurmans, Hanjun Dai

ICLR 2023 Score-Based Continuous-Time Discrete Diffusion Models Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai

NeurIPS 2023 Video Timeline Modeling for News Story Understanding Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong

NeurIPSW 2022 Annealed Training for Combinatorial Optimization on Graphs Haoran Sun, Etash Kumar Guha, Hanjun Dai

ICLR 2022 CodeTrek: Flexible Modeling of Code Using an Extensible Relational Representation Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik

ICLR 2022 CrossBeam: Learning to Search in Bottom-up Program Synthesis Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton

NeurIPS 2022 Does GNN Pretraining Help Molecular Representation? Ruoxi Sun, Hanjun Dai, Adams Wei Yu

ICLRW 2022 Learning to Walk over Relational Graphs of Source Code Pardis Pashakhanloo, Aaditya Naik, Hanjun Dai, Petros Maniatis, Mayur Naik

ICML 2022 Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai

ICLR 2022 Neural Stochastic Dual Dynamic Programming Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai

NeurIPS 2022 Optimal Scaling for Locally Balanced Proposals in Discrete Spaces Haoran Sun, Hanjun Dai, Dale Schuurmans

ICLR 2022 Path Auxiliary Proposal for MCMC in Discrete Space Haoran Sun, Hanjun Dai, Wei Xia, Arun Ramamurthy

ICLR 2021 BUSTLE: Bottom-up Program Synthesis Through Learning-Guided Exploration Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai

NeurIPS 2021 Combiner: Full Attention Transformer with Sparse Computation Cost Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai

ICML 2021 LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou

ICLR 2021 Molecule Optimization by Explainable Evolution Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song

ICML 2021 SpreadsheetCoder: Formula Prediction from Semi-Structured Context Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou

NeurIPS 2021 Towards Understanding Retrosynthesis by Energy-Based Models Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai

NeurIPSW 2020 A Framework for Differentiable Discovery of Graph Algorithms Hanjun Dai, Xinshi Chen, Yu Li, Xin Gao, Le Song

NeurIPSW 2020 Differentiable Top-$k$ with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

NeurIPS 2020 Differentiable Top-K with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

ICML 2020 Energy-Based Processes for Exchangeable Data Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans

ICLR 2020 Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang

NeurIPS 2020 Learning Discrete Energy-Based Models via Auxiliary-Variable Local Exploration Hanjun Dai, Rishabh Singh, Bo Dai, Charles A. Sutton, Dale Schuurmans

ICML 2020 Learning to Stop While Learning to Predict Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song

ICML 2020 Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search Binghong Chen, Chengtao Li, Hanjun Dai, Le Song

ICML 2020 Scalable Deep Generative Modeling for Sparse Graphs Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans

ICML 2019 CompILE: Compositional Imitation Learning and Execution Thomas Kipf, Yujia Li, Hanjun Dai, Vinicius Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter Battaglia

NeurIPS 2019 Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans

AISTATS 2019 Kernel Exponential Family Estimation via Doubly Dual Embedding Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He

NeurIPS 2019 Learning Transferable Graph Exploration Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli

ICLR 2019 Learning a Meta-Solver for Syntax-Guided Program Synthesis Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song

ICML 2019 Particle Flow Bayes’ Rule Xinshi Chen, Hanjun Dai, Le Song

NeurIPS 2019 Retrosynthesis Prediction with Conditional Graph Logic Network Hanjun Dai, Chengtao Li, Connor Coley, Bo Dai, Le Song

ICML 2018 Adversarial Attack on Graph Structured Data Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song

NeurIPS 2018 Cooperative Neural Networks (CoNN): Exploiting Prior Independence Structure for Improved Classification Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru

NeurIPS 2018 Coupled Variational Bayes via Optimization Embedding Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

NeurIPS 2018 Learning Loop Invariants for Program Verification Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, Le Song

ICML 2018 Learning Steady-States of Iterative Algorithms over Graphs Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alex Smola, Le Song

ICLR 2018 Syntax-Directed Variational Autoencoder for Structured Data Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song

AAAI 2018 Variational Reasoning for Question Answering with Knowledge Graph Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song

ICML 2017 Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song

NeurIPS 2017 Learning Combinatorial Optimization Algorithms over Graphs Elias Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, Le Song

ICLR 2017 Recurrent Hidden Semi-Markov Model Hanjun Dai, Bo Dai, Yan-Ming Zhang, Shuang Li, Le Song

ICML 2016 Discriminative Embeddings of Latent Variable Models for Structured Data Hanjun Dai, Bo Dai, Le Song

AISTATS 2016 Provable Bayesian Inference via Particle Mirror Descent Bo Dai, Niao He, Hanjun Dai, Le Song

NeurIPS 2015 M-Statistic for Kernel Change-Point Detection Shuang Li, Yao Xie, Hanjun Dai, Le Song

AAAI 2014 Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu