Hanjun Dai

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 112

Top Venues

CoRR

NeurIPS

ICML

ICLR

Publications

Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models. CoRR (2024)
Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
UQE: A Query Engine for Unstructured Databases. CoRR (2024)
Chang Zhu, Ziyang Li, Anton Xue, Ati Priya Bajaj, Wil Gibbs, Yibo Liu, Rajeev Alur, Tiffany Bao, Hanjun Dai, Adam Doupé, Mayur Naik, Yan Shoshitaishvili, Ruoyu Wang, Aravind Machiry
TYGR: Type Inference on Stripped Binaries using Graph Neural Networks. USENIX Security Symposium (2024)
Bernd Bohnet, Azade Nova, Aaron T. Parisi, Kevin Swersky, Katayoon Goshvadi, Hanjun Dai, Dale Schuurmans, Noah Fiedel, Hanie Sedghi
Exploring and Benchmarking the Planning Capabilities of Large Language Models. CoRR (2024)
Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai
Beyond Expectations: Learning with Stochastic Dominance Made Practical. CoRR (2024)
Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. CoRR (2024)
Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
Video Timeline Modeling For News Story Understanding. NeurIPS (2023)
Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. EMNLP (Findings) (2023)
Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai
Learning to Optimize with Stochastic Dominance Constraints. AISTATS (2023)
Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister
Better Zero-Shot Reasoning with Self-Adaptive Prompting. ACL (Findings) (2023)
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. EMNLP (Findings) (2023)
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arik, Tomas Pfister
Universal Self-adaptive Prompting. CoRR (2023)
Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. CoRR (2023)
Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister
Better Zero-Shot Reasoning with Self-Adaptive Prompting. CoRR (2023)
Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
Score-based Continuous-time Discrete Diffusion Models. ICLR (2023)
Lijun Yu, Jin Miao, Xiaoyu Sun, Jiayi Chen, Alexander G. Hauptmann, Hanjun Dai, Wei Wei
Document Entity Retrieval with Massive and Noisy Pre-training. CoRR (2023)
Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel
Learning Universal Policies via Text-Guided Video Generation. NeurIPS (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS (2023)
Zhaocheng Zhu, Yuan Xue, Xinyun Chen, Denny Zhou, Jian Tang, Dale Schuurmans, Hanjun Dai
Large Language Models can Learn Rules. CoRR (2023)
Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. CoRR (2023)
Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. NeurIPS (2023)
Azade Nova, Hanjun Dai, Dale Schuurmans
Gradient-Free Structured Pruning with Unlabeled Data. ICML (2023)
Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
Discrete Langevin Samplers via Wasserstein Gradient Flow. AISTATS (2023)
Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai
Any-scale Balanced Samplers for Discrete Space. ICLR (2023)
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister
Universal Self-Adaptive Prompting. EMNLP (2023)
Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai
DISCS: A Benchmark for Discrete Sampling. NeurIPS (2023)
Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel
Learning Universal Policies via Text-Guided Video Generation. CoRR (2023)
Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
Video Timeline Modeling For News Story Understanding. CoRR (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR (2023)
Lijun Yu, Jin Miao, Xiaoyu Sun, Jiayi Chen, Alexander G. Hauptmann, Hanjun Dai, Wei Wei
DocumentNet: Bridging the Data Gap in Document Pre-training. EMNLP (Industry Track) (2023)
Azade Nova, Hanjun Dai, Dale Schuurmans
Gradient-Free Structured Pruning with Unlabeled Data. CoRR (2023)
Haoran Sun, Katayoon Goshvadi, Azade Nova, Dale Schuurmans, Hanjun Dai
Revisiting Sampling for Combinatorial Optimization. ICML (2023)
Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL. CoRR (2023)
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. CoRR (2023)
Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. ICLR (2022)
Haoran Sun, Hanjun Dai, Dale Schuurmans
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces. CoRR (2022)
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. KDD (2022)
Haoran Sun, Hanjun Dai, Dale Schuurmans
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces. NeurIPS (2022)
Haoran Sun, Hanjun Dai, Wei Xia, Arun Ramamurthy
Path Auxiliary Proposal for MCMC in Discrete Space. ICLR (2022)
Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai
Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization. ICML (2022)
Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
CrossBeam: Learning to Search in Bottom-Up Program Synthesis. CoRR (2022)
Ruoxi Sun, Hanjun Dai, Adams Wei Yu
Does GNN Pretraining Help Molecular Representation? NeurIPS (2022)
Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik
CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. ICLR (2022)
Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
Score-based Continuous-time Discrete Diffusion Models. CoRR (2022)
Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
Neural Stochastic Dual Dynamic Programming. ICLR (2022)
Haoran Sun, Etash K. Guha, Hanjun Dai
Annealed Training for Combinatorial Optimization on Graphs. CoRR (2022)
Hanjun Dai, Yuan Xue, Niao He, Bethany Wang, Na Li, Dale Schuurmans, Bo Dai
Learning to Optimize with Stochastic Dominance Constraints. CoRR (2022)
Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
Discrete Langevin Sampler via Wasserstein Gradient Flow. CoRR (2022)
Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
Combiner: Full Attention Transformer with Sparse Computation Cost. CoRR (2021)
Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
Towards understanding retrosynthesis by energy-based models. NeurIPS (2021)
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
SpreadsheetCoder: Formula Prediction from Semi-structured Context. CoRR (2021)
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou
LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs. ICML (2021)
Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
Neural Stochastic Dual Dynamic Programming. CoRR (2021)
Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
Combiner: Full Attention Transformer with Sparse Computation Cost. NeurIPS (2021)
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration. ICLR (2021)
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. CoRR (2021)
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
SpreadsheetCoder: Formula Prediction from Semi-structured Context. ICML (2021)
Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song
Molecule Optimization by Explainable Evolution. ICLR (2021)
Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
Energy-Based Processes for Exchangeable Data. CoRR (2020)
Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
Retrosynthesis Prediction with Conditional Graph Logic Network. CoRR (2020)
Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
Scalable Deep Generative Modeling for Sparse Graphs. ICML (2020)
Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
Energy-Based Processes for Exchangeable Data. ICML (2020)
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. CoRR (2020)
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Learning to Stop While Learning to Predict. CoRR (2020)
Rohit Batra, Hanjun Dai, Tran Doan Huan, Lihua Chen, Chiho Kim, Will R. Gutekunst, Le Song, Rampi Ramprasad
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders. CoRR (2020)
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. NeurIPS (2020)
Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
Differentiable Top-k Operator with Optimal Transport. CoRR (2020)
Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. ICLR (2020)
Binghong Chen, Chengtao Li, Hanjun Dai, Le Song
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. ICML (2020)
Binghong Chen, Chengtao Li, Hanjun Dai, Le Song
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. CoRR (2020)
Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
Scalable Deep Generative Modeling for Sparse Graphs. CoRR (2020)
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Learning To Stop While Learning To Predict. ICML (2020)
Xujie Si, Aaditya Naik, Hanjun Dai, Mayur Naik, Le Song
Code2Inv: A Deep Learning Framework for Program Verification. CAV (2) (2020)
Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
Differentiable Top-k with Optimal Transport. NeurIPS (2020)
Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
Energy-based View of Retrosynthesis. CoRR (2020)
Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
Retrosynthesis Prediction with Conditional Graph Logic Network. NeurIPS (2019)
Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia
CompILE: Compositional Imitation Learning and Execution. ICML (2019)
Xinshi Chen, Hanjun Dai, Le Song
Meta Particle Flow for Sequential Bayesian Inference. CoRR (2019)
Xinshi Chen, Hanjun Dai, Le Song
Particle Flow Bayes' Rule. ICML (2019)
Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
Kernel Exponential Family Estimation via Doubly Dual Embedding. AISTATS (2019)
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
Learning Transferable Graph Exploration. CoRR (2019)
Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
Exponential Family Estimation via Adversarial Dynamics Embedding. CoRR (2019)
Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. CoRR (2019)
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
Learning Transferable Graph Exploration. NeurIPS (2019)
Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song
Learning a Meta-Solver for Syntax-Guided Program Synthesis. ICLR (Poster) (2019)
Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
Exponential Family Estimation via Adversarial Dynamics Embedding. NeurIPS (2019)
Yuyu Zhang, Hanjun Dai, Kamil Toraman, Le Song
KG^2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings. CoRR (2018)
Feng Wang, Weiyang Liu, Hanjun Dai, Haijun Liu, Jian Cheng
Additive Margin Softmax for Face Verification. ICLR (Workshop) (2018)
Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, Le Song
Learning Loop Invariants for Program Verification. NeurIPS (2018)
Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song
Coupled Variational Bayes via Optimization Embedding. NeurIPS (2018)
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song
Adversarial Attack on Graph Structured Data. ICML (2018)
Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
Syntax-Directed Variational Autoencoder for Structured Data. ICLR (Poster) (2018)
Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
Kernel Exponential Family Estimation via Doubly Dual Embedding. CoRR (2018)
Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. NeurIPS (2018)
Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia
Compositional Imitation Learning: Explaining and executing one task at a time. CoRR (2018)
Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song
Learning Steady-States of Iterative Algorithms over Graphs. ICML (2018)
Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
Variational Reasoning for Question Answering With Knowledge Graph. AAAI (2018)
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song
Adversarial Attack on Graph Structured Data. CoRR (2018)
Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
Syntax-Directed Variational Autoencoder for Structured Data. CoRR (2018)
Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, Le Song
Learning Combinatorial Optimization Algorithms over Graphs. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hanjun Dai