Prior-Free Exploration Bonus for and beyond Near Bayes-Optimal Behavior. - Kenji Kawaguchi; Hiroshi Sato (IJCAI, 2013)

A Greedy Approximation of Bayesian Reinforcement Learning with Probably Optimistic Transition Model - Kenji Kawaguchi; Mauricio Araya-López (CoRR, 2013)

Bayesian Optimization with Exponential Convergence. - Kenji Kawaguchi; Leslie Pack Kaelbling; Tomás Lozano-Pérez (NIPS, 2015)

Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident. - Xiaoyu Zheng; Hiroto Itoh; Kenji Kawaguchi; Hitoshi Tamaki; Yu Maruyama (Reliab. Eng. Syst. Saf., 2015)

Bounded Optimal Exploration in MDP. - Kenji Kawaguchi (AAAI, 2016)

Deep Learning without Poor Local Minima. - Kenji Kawaguchi (NIPS, 2016)

Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning. - Qianli Liao; Kenji Kawaguchi; Tomaso A. Poggio (CoRR, 2016)

Global Continuous Optimization with Error Bound and Fast Convergence. - Kenji Kawaguchi; Yu Maruyama; Xiaoyu Zheng (J. Artif. Intell. Res., 2016)

Depth Creates No Bad Local Minima. - Haihao Lu; Kenji Kawaguchi (CoRR, 2017)

Generalization in Deep Learning. - Kenji Kawaguchi; Leslie Pack Kaelbling; Yoshua Bengio (CoRR, 2017)

Deep Semi-Random Features for Nonlinear Function Approximation. - Kenji Kawaguchi; Bo Xie 002; Le Song (AAAI, 2018)

Theory of Deep Learning III: explaining the non-overfitting puzzle. - Tomaso A. Poggio; Kenji Kawaguchi; Qianli Liao; Brando Miranda; Lorenzo Rosasco; Xavier Boix; Jack Hidary; Hrushikesh N. Mhaskar (CoRR, 2018)

Generalization in Machine Learning via Analytical Learning Theory. - Kenji Kawaguchi; Yoshua Bengio (CoRR, 2018)

Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes. - Kenji Kawaguchi; Jiaoyang Huang (Allerton, 2019)

Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit. - Jascha Sohl-Dickstein; Kenji Kawaguchi (CoRR, 2019)

Every Local Minimum is a Global Minimum of an Induced Model. - Kenji Kawaguchi; Leslie Pack Kaelbling (CoRR, 2019)

A Stochastic First-Order Method for Ordered Empirical Risk Minimization. - Kenji Kawaguchi; Haihao Lu (CoRR, 2019)

Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks. - Ameya D. Jagtap; Kenji Kawaguchi; George E. Karniadakis (CoRR, 2019)

Effect of Depth and Width on Local Minima in Deep Learning. - Kenji Kawaguchi; Jiaoyang Huang; Leslie Pack Kaelbling (Neural Comput., 2019)

Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning. - Kenji Kawaguchi; Jiaoyang Huang; Leslie Pack Kaelbling (Neural Comput., 2019)

Depth with nonlinearity creates no bad local minima in ResNets. - Kenji Kawaguchi; Yoshua Bengio (Neural Networks, 2019)

Elimination of All Bad Local Minima in Deep Learning. - Kenji Kawaguchi; Leslie Pack Kaelbling (AISTATS, 2020)

Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization. - Kenji Kawaguchi; Haihao Lu (AISTATS, 2020)

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time. - Ferran Alet; Kenji Kawaguchi; Tomás Lozano-Pérez; Leslie Pack Kaelbling (CoRR, 2020)

Towards Domain-Agnostic Contrastive Learning. - Vikas Verma; Minh-Thang Luong; Kenji Kawaguchi; Hieu Pham 001; Quoc V. Le (CoRR, 2020)

Adaptive activation functions accelerate convergence in deep and physics-informed neural networks. - Ameya D. Jagtap; Kenji Kawaguchi; George Em Karniadakis (J. Comput. Phys., 2020)

A Recipe for Global Convergence Guarantee in Deep Neural Networks. - Kenji Kawaguchi; Qingyun Sun (AAAI, 2021)

GraphMix: Improved Training of GNNs for Semi-Supervised Learning. - Vikas Verma; Meng Qu; Kenji Kawaguchi; Alex Lamb; Yoshua Bengio; Juho Kannala; Jian Tang 005 (AAAI, 2021)

How Shrinking Gradient Noise Helps the Performance of Neural Networks. - Zhun Deng; Jiaoyang Huang; Kenji Kawaguchi (IEEE BigData, 2021)

On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers. - Kenji Kawaguchi (ICLR, 2021)

How Does Mixup Help With Robustness and Generalization? - Linjun Zhang; Zhun Deng; Kenji Kawaguchi; Amirata Ghorbani; James Zou 001 (ICLR, 2021)

Towards Domain-Agnostic Contrastive Learning. - Vikas Verma; Thang Luong; Kenji Kawaguchi; Hieu Pham 001; Quoc V. Le (ICML, 2021)

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth. - Keyulu Xu; Mozhi Zhang; Stefanie Jegelka; Kenji Kawaguchi (ICML, 2021)

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time. - Ferran Alet; Maria Bauzá 001; Kenji Kawaguchi; Nurullah Giray Kuru; Tomás Lozano-Pérez; Leslie Pack Kaelbling (NeurIPS, 2021)

Noether Networks: meta-learning useful conserved quantities. - Ferran Alet; Dylan Doblar; Allan Zhou; Josh Tenenbaum 001; Kenji Kawaguchi; Chelsea Finn (NeurIPS, 2021)

Adversarial Training Helps Transfer Learning via Better Representations. - Zhun Deng; Linjun Zhang; Kailas Vodrahalli; Kenji Kawaguchi; James Y. Zou (NeurIPS, 2021)

Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization. - Clement Gehring; Kenji Kawaguchi; Jiaoyang Huang; Leslie Pack Kaelbling (NeurIPS, 2021)

EIGNN: Efficient Infinite-Depth Graph Neural Networks. - Juncheng Liu; Kenji Kawaguchi; Bryan Hooi; Yiwei Wang 001; Xiaokui Xiao (NeurIPS, 2021)

Discrete-Valued Neural Communication. - Dianbo Liu; Alex Lamb; Kenji Kawaguchi; Anirudh Goyal; Chen Sun 007; Michael C. Mozer; Yoshua Bengio (NeurIPS, 2021)

CAC: A Clustering Based Framework for Classification. - Shivin Srivastava; Siddharth Bhatia 001; Lingxiao Huang; Lim Jun Heng; Kenji Kawaguchi; Vaibhav Rajan (CoRR, 2021)

MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift. - Siddharth Bhatia 001; Arjit Jain; Shivin Srivastava; Kenji Kawaguchi; Bryan Hooi (CoRR, 2021)

Robustness Implies Generalization via Data-Dependent Generalization Bounds. - Kenji Kawaguchi; Zhun Deng; Kyle Luh; Jiaoyang Huang (ICML, 2022)

Multi-Task Learning as a Bargaining Game. - Aviv Navon; Aviv Shamsian; Idan Achituve; Haggai Maron; Kenji Kawaguchi; Gal Chechik; Ethan Fetaya (ICML, 2022)

When and How Mixup Improves Calibration. - Linjun Zhang; Zhun Deng; Kenji Kawaguchi; James Zou 001 (ICML, 2022)

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (NeurIPS, 2022)

Set-based Meta-Interpolation for Few-Task Meta-Learning. - Seanie Lee; Bruno Andreis; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (NeurIPS, 2022)

MGNNI: Multiscale Graph Neural Networks with Implicit Layers. - Juncheng Liu; Bryan Hooi; Kenji Kawaguchi; Xiaokui Xiao (NeurIPS, 2022)

MemStream: Memory-Based Streaming Anomaly Detection. - Siddharth Bhatia 001; Arjit Jain; Shivin Srivastava; Kenji Kawaguchi; Bryan Hooi (WWW, 2022)

Training Free Graph Neural Networks for Graph Matching. - Zhiyuan Liu 001; Yixin Cao 002; Fuli Feng; Xiang Wang 010; Xindi Shang; Jie Tang 001; Kenji Kawaguchi; Tat-Seng Chua (CoRR, 2022)

ExpertNet: A Symbiosis of Classification and Clustering. - Shivin Srivastava; Kenji Kawaguchi; Vaibhav Rajan (CoRR, 2022)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Notsawo; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (CoRR, 2022)

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. - Samuel Lavoie; Christos Tsirigotis; Max Schwarzer; Kenji Kawaguchi; Ankit Vani; Aaron C. Courville (CoRR, 2022)

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (CoRR, 2022)

Neural Active Learning on Heteroskedastic Distributions. - Savya Khosla; Chew Kin Whye; Jordan T. Ash; Cyril Zhang; Kenji Kawaguchi; Alex Lamb (CoRR, 2022)

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. - Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham 001; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (CoRR, 2022)

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. - Ameya D. Jagtap; Yeonjong Shin; Kenji Kawaguchi; George Em Karniadakis (Neurocomputing, 2022)

Meta-learning PINN loss functions. - Apostolos F. Psaros; Kenji Kawaguchi; George Em Karniadakis (J. Comput. Phys., 2022)

Understanding Dynamics of Nonlinear Representation Learning and Its Application. - Kenji Kawaguchi; Linjun Zhang; Zhun Deng (Neural Comput., 2022)

Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. - Alex Lamb; Vikas Verma; Kenji Kawaguchi; Alexander Matyasko; Savya Khosla; Juho Kannala; Yoshua Bengio (Neural Networks, 2022)

Interpolation consistency training for semi-supervised learning. - Vikas Verma; Kenji Kawaguchi; Alex Lamb; Juho Kannala; Arno Solin; Yoshua Bengio; David Lopez-Paz (Neural Networks, 2022)

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? - Zheyuan Hu 002; Ameya D. Jagtap; George Em Karniadakis; Kenji Kawaguchi (SIAM J. Sci. Comput., 2022)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Tikeng Notsawo Jr.; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (AAAI, 2023)

Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. - Savya Khosla; Chew Kin Whye; Jordan T. Ash; Cyril Zhang; Kenji Kawaguchi; Alex Lamb (ECAI, 2023)

MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. - Zhiyuan Liu 001; Sihang Li 002; Yanchen Luo; Hao Fei 001; Yixin Cao 002; Kenji Kawaguchi; Xiang Wang 010; Tat-Seng Chua (EMNLP, 2023)

Automatic Model Selection with Large Language Models for Reasoning. - James Xu Zhao; Yuxi Xie; Kenji Kawaguchi; Junxian He; Michael Qizhe Xie (EMNLP (Findings), 2023)

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. - Samuel Lavoie; Christos Tsirigotis; Max Schwarzer; Ankit Vani; Michael Noukhovitch; Kenji Kawaguchi; Aaron C. Courville (ICLR, 2023)

Self-Distillation for Further Pre-training of Transformers. - Seanie Lee; Minki Kang; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi (ICLR, 2023)

Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. - Dong Bok Lee; Seanie Lee; Kenji Kawaguchi; Yunji Kim; Jihwan Bang; Jung-Woo Ha 001; Sung Ju Hwang (ICLR, 2023)

D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. - Tianbo Li; Min Lin; Zheyuan Hu 002; Kunhao Zheng; Giovanni Vignale; Kenji Kawaguchi; A. H. Castro Neto; Kostya S. Novoselov; Shuicheng Yan (ICLR, 2023)

How Does Information Bottleneck Help Deep Learning? - Kenji Kawaguchi; Zhun Deng; Xu Ji; Jiaoyang Huang (ICML, 2023)

GFlowOut: Dropout with Generative Flow Networks. - Dianbo Liu; Moksh Jain; Bonaventure F. P. Dossou; Qianli Shen; Salem Lahlou; Anirudh Goyal; Nikolay Malkin; Chris Chinenye Emezue; Dinghuai Zhang; Nadhir Hassen; Xu Ji; Kenji Kawaguchi; et al. (ICML, 2023)

Auxiliary Learning as an Asymmetric Bargaining Game. - Aviv Shamsian; Aviv Navon; Neta Glazer; Kenji Kawaguchi; Gal Chechik; Ethan Fetaya (ICML, 2023)

Discrete Key-Value Bottleneck. - Frederik Träuble; Anirudh Goyal; Nasim Rahaman; Michael Curtis Mozer; Kenji Kawaguchi; Yoshua Bengio; Bernhard Schölkopf (ICML, 2023)

Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. - Jeffrey Willette; Seanie Lee; Bruno Andreis; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (ICML, 2023)

Sketch-Based Anomaly Detection in Streaming Graphs. - Siddharth Bhatia 001; Mohit Wadhwa; Kenji Kawaguchi; Neil Shah; Philip S. Yu; Bryan Hooi (KDD, 2023)

Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. - Minki Kang; Seanie Lee; Jinheon Baek; Kenji Kawaguchi; Sung Ju Hwang (NeurIPS, 2023)

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. - Zhiyuan Liu 001; Yaorui Shi; An Zhang 003; Enzhi Zhang; Kenji Kawaguchi; Xiang Wang 010; Tat-Seng Chua (NeurIPS, 2023)

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. - Qianli Shen; Wai Hoh Tang; Zhun Deng; Apostolos F. Psaros; Kenji Kawaguchi (NeurIPS, 2023)

An Information Theory Perspective on Variance-Invariance-Covariance Regularization. - Ravid Shwartz-Ziv; Randall Balestriero; Kenji Kawaguchi; Tim G. J. Rudner; Yann LeCun (NeurIPS, 2023)

Self-Evaluation Guided Beam Search for Reasoning. - Yuxi Xie; Kenji Kawaguchi; Yiran Zhao 006; James Xu Zhao; Min-Yen Kan; Junxian He; Michael Qizhe Xie (NeurIPS, 2023)

MixupE: Understanding and improving Mixup from directional derivative perspective. - Yingtian Zou; Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham 001; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (UAI, 2023)

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. - Ravid Shwartz-Ziv; Randall Balestriero; Kenji Kawaguchi; Tim G. J. Rudner; Yann LeCun (CoRR, 2023)

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. - Yuzhen Mao; Zhun Deng; Huaxiu Yao; Ting Ye; Kenji Kawaguchi; James Zou 001 (CoRR, 2023)

Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding. - Yuxi Xie; Kenji Kawaguchi; Yiran Zhao 006; Xu Zhao; Min-Yen Kan; Junxian He; Qizhe Xie (CoRR, 2023)

Automatic Model Selection with Large Language Models for Reasoning. - Xu Zhao; Yuxi Xie; Kenji Kawaguchi; Junxian He; Qizhe Xie (CoRR, 2023)

Fast Diffusion Model. - Zike Wu; Pan Zhou 002; Kenji Kawaguchi; Hanwang Zhang (CoRR, 2023)

IF2Net: Innately Forgetting-Free Networks for Continual Learning. - Depeng Li 001; Tianqi Wang; Bingrong Xu; Kenji Kawaguchi; Zhigang Zeng; Ponnuthurai Nagaratnam Suganthan (CoRR, 2023)

AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments. - Yang Zhang; Yawei Li; Hannah Brown; Mina Rezaei; Bernd Bischl; Philip H. S. Torr; Ashkan Khakzar; Kenji Kawaguchi (CoRR, 2023)

ChOiRe: Characterizing and Predicting Human Opinions with Chain of Opinion Reasoning. - Xuan Long Do; Kenji Kawaguchi; Min-Yen Kan; Nancy F. Chen (CoRR, 2023)

Investigating Copyright Issues of Diffusion Models under Practical Scenarios. - Yang Zhang; Teoh Tze Tzun; Lim Wei Hern; Haonan Wang; Kenji Kawaguchi (CoRR, 2023)

Probabilistic Copyright Protection Can Fail for Text-to-Image Generative Models. - Xiang Li; Qianli Shen; Kenji Kawaguchi (CoRR, 2023)

Learning Unorthogonalized Matrices for Rotation Estimation. - Kerui Gu; Zhihao Li 002; Shiyong Liu; Jianzhuang Liu; Songcen Xu; Youliang Yan; Michael Bi Mi; Kenji Kawaguchi; Angela Yao (CoRR, 2023)

Prompt Optimization via Adversarial In-Context Learning. - Xuan Long Do; Yiran Zhao 006; Hannah Brown; Yuxi Xie; James Xu Zhao; Nancy F. Chen; Kenji Kawaguchi; Michael Qizhe Xie; Junxian He (CoRR, 2023)

Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks. - Zheyuan Hu 002; Zekun Shi; George Em Karniadakis; Kenji Kawaguchi (CoRR, 2023)

Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph. - Haonan Wang; Jieyu Zhang 001; Qi Zhu 008; Wei Huang; Kenji Kawaguchi; Xiaokui Xiao (Trans. Mach. Learn. Res., 2023)

Combined scaling for zero-shot transfer learning. - Hieu Pham 001; Zihang Dai; Golnaz Ghiasi; Kenji Kawaguchi; Hanxiao Liu; Adams Wei Yu; Jiahui Yu; Yi-Ting Chen; Minh-Thang Luong; Yonghui Wu; Mingxing Tan; Quoc V. Le (Neurocomputing, 2023)

Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology. - Zheyuan Hu 002; Ameya D. Jagtap; George Em Karniadakis; Kenji Kawaguchi (Eng. Appl. Artif. Intell., 2023)

Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding. - Depeng Li 001; Tianqi Wang; Junwei Chen; Qining Ren; Kenji Kawaguchi; Zhigang Zeng (AAAI, 2024)

ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining. - Zhiyuan Liu 001; Yaorui Shi; An Zhang 003; Sihang Li 002; Enzhi Zhang; Xiang Wang 010; Kenji Kawaguchi; Tat-Seng Chua (ACL (Findings), 2024)

ProtT3: Protein-to-Text Generation for Text-based Protein Understanding. - Zhiyuan Liu 001; An Zhang 003; Hao Fei 001; Enzhi Zhang; Xiang Wang 010; Kenji Kawaguchi; Tat-Seng Chua (ACL (1), 2024)

Prompt Optimization via Adversarial In-Context Learning. - Do Xuan Long; Yiran Zhao 006; Hannah Brown; Yuxi Xie; James Xu Zhao; Nancy F. Chen; Kenji Kawaguchi; Michael Shieh; Junxian He (ACL (1), 2024)

VA3: Virtually Assured Amplification Attack on Probabilistic Copyright Protection for Text-to-Image Generative Models. - Xiang Li; Qianli Shen; Kenji Kawaguchi (CVPR, 2024)

Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models. - Yang Zhang; Teoh Tze Tzun; Lim Wei Hern; Kenji Kawaguchi (ECCV (86), 2024)

Reasoning Robustness of LLMs to Adversarial Typographical Errors. - Esther Gan; Yiran Zhao 006; Liying Cheng; Yancan Mao; Anirudh Goyal; Kenji Kawaguchi; Min-Yen Kan; Michael Shieh (EMNLP, 2024)

Multi-expert Prompting Improves Reliability, Safety and Usefulness of Large Language Models. - Do Xuan Long; Duong Ngoc Yen; Anh Tuan Luu; Kenji Kawaguchi; Min-Yen Kan; Nancy F. Chen (EMNLP, 2024)

Simple Hierarchical Planning with Diffusion. - Chang Chen; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICLR, 2024)

Self-Supervised Dataset Distillation for Transfer Learning. - Dong Bok Lee; Seanie Lee; Joonho Ko; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (ICLR, 2024)

Towards 3D Molecule-Text Interpretation in Language Models. - Sihang Li 002; Zhiyuan Liu 001; Yanchen Luo; Xiang Wang 010; Xiangnan He 001; Kenji Kawaguchi; Tat-Seng Chua; Qi Tian 001 (ICLR, 2024)

Scalable and Effective Implicit Graph Neural Networks on Large Graphs. - Juncheng Liu; Bryan Hooi; Kenji Kawaguchi; Yiwei Wang 001; Chaosheng Dong; Xiaokui Xiao (ICLR, 2024)

Towards Robust Out-of-Distribution Generalization Bounds via Sharpness. - Yingtian Zou; Kenji Kawaguchi; Yingnan Liu 002; Jiashuo Liu; Mong-Li Lee; Wynne Hsu (ICLR, 2024)

Unsupervised Concept Discovery Mitigates Spurious Correlations. - Md Rifat Arefin; Yan Zhang; Aristide Baratin; Francesco Locatello; Irina Rish; Dianbo Liu; Kenji Kawaguchi (ICML, 2024)

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. - Chang Chen; Junyeob Baek; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICML, 2024)

Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. - Brian K. Chen; Tianyang Hu; Hui Jin; Hwee Kuan Lee; Kenji Kawaguchi (ICML, 2024)

Drug Discovery with Dynamic Goal-aware Fragments. - Seul Lee; Seanie Lee; Kenji Kawaguchi; Sung Ju Hwang (ICML, 2024)

Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. - Xuantong Liu; Tianyang Hu; Wenjia Wang; Kenji Kawaguchi; Yuan Yao 011 (ICML, 2024)

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. - Jiajun Ma; Shuchen Xue; Tianyang Hu; Wenjia Wang; Zhaoqiang Liu; Zhenguo Li; Zhi-Ming Ma; Kenji Kawaguchi (ICML, 2024)

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline. - Haonan Wang; Qianli Shen; Yao Tong; Yang Zhang; Kenji Kawaguchi (ICML, 2024)

Deep Regression Representation Learning with Topology. - Shihao Zhang; Kenji Kawaguchi; Angela Yao (ICML, 2024)

How do Large Language Models Handle Multilingualism? - Yiran Zhao 006; Wenxuan Zhang 001; Guizhen Chen; Kenji Kawaguchi; Lidong Bing (NeurIPS, 2024)

Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling. - Yiran Zhao 006; Wenyue Zheng; Tianle Cai; Do Xuan Long; Kenji Kawaguchi; Anirudh Goyal; Michael Qizhe Shieh (NeurIPS, 2024)

Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. - Qianli Shen; Yezhen Wang; Zhouhao Yang; Xiang Li; Haonan Wang; Yang Zhang; Jonathan Scarlett; Zhanxing Zhu; Kenji Kawaguchi (NeurIPS, 2024)

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators. - Zekun Shi; Zheyuan Hu 002; Min Lin; Kenji Kawaguchi (NeurIPS, 2024)

Can AI Be as Creative as Humans? - Haonan Wang; James Zou 001; Michael Mozer; Anirudh Goyal; Alex Lamb; Linjun Zhang; Weijie J. Su; Zhun Deng; Michael Qizhe Xie; Hannah Brown; Kenji Kawaguchi (CoRR, 2024)

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline. - Haonan Wang; Qianli Shen; Yao Tong; Yang Zhang; Kenji Kawaguchi (CoRR, 2024)

Accelerating Greedy Coordinate Gradient via Probe Sampling. - Yiran Zhao 006; Wenyue Zheng; Tianle Cai; Xuan Long Do; Kenji Kawaguchi; Anirudh Goyal; Michael Shieh (CoRR, 2024)

Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models. - Yang Zhang; Teoh Tze Tzun; Lim Wei Hern; Tiviatis Sim; Kenji Kawaguchi (CoRR, 2024)

Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning. - Yuxi Xie; Anirudh Goyal; Wenyue Zheng; Min-Yen Kan; Timothy P. Lillicrap; Kenji Kawaguchi; Michael Shieh (CoRR, 2024)

FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models. - Yang Zhang; Yawei Li; Xinpeng Wang 003; Qianli Shen; Barbara Plank; Bernd Bischl; Mina Rezaei; Kenji Kawaguchi (CoRR, 2024)

Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations. - Zheyuan Hu 002; Zhongqiang Zhang; George Em Karniadakis; Kenji Kawaguchi (CoRR, 2024)

Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks. - Zheyuan Hu 002; Kenji Kawaguchi; Zhongqiang Zhang; George Em Karniadakis (CoRR, 2024)

Self-Evaluation as a Defense Against Adversarial Attacks on LLMs. - Hannah Brown; Leon Lin; Kenji Kawaguchi; Michael Shieh (CoRR, 2024)

State-space models are accurate and efficient neural operators for dynamical systems. - Zheyuan Hu 002; Nazanin Ahmadi Daryakenari; Qianli Shen; Kenji Kawaguchi; George Em Karniadakis (CoRR, 2024)

Investigating Layer Importance in Large Language Models. - Yang Zhang; Yanfei Dong; Kenji Kawaguchi (CoRR, 2024)

Effortless Efficiency: Low-Cost Pruning of Diffusion Models. - Yang Zhang; Er Jin; Yanfei Dong; Ashkan Khakzar; Philip Torr 001; Johannes Stegmaier; Kenji Kawaguchi (CoRR, 2024)

Functional Risk Minimization. - Ferran Alet; Clement Gehring; Tomás Lozano-Pérez; Kenji Kawaguchi; Joshua B. Tenenbaum; Leslie Pack Kaelbling (CoRR, 2024)

Tackling the curse of dimensionality with physics-informed neural networks. - Zheyuan Hu 002; Khemraj Shukla; George Em Karniadakis; Kenji Kawaguchi (Neural Networks, 2024)

A Dual-Perspective Approach to Evaluating Feature Attribution Methods. - Yawei Li; Yang Zhang; Kenji Kawaguchi; Ashkan Khakzar; Bernd Bischl; Mina Rezaei (Trans. Mach. Learn. Res., 2024)

Multi-view class incremental learning. - Depeng Li 001; Tianqi Wang; Junwei Chen; Kenji Kawaguchi; Cheng Lian; Zhigang Zeng (Inf. Fusion, 2024)

Single Character Perturbations Break LLM Alignment. - Leon Lin; Hannah Brown; Kenji Kawaguchi; Michael Shieh (AAAI, 2025)

What Makes a Good Natural Language Prompt? - Do Xuan Long; Duy Dinh; Ngoc-Hai Nguyen; Kenji Kawaguchi; Nancy F. Chen; Shafiq Joty; Min-Yen Kan (ACL (1), 2025)

Beyond In-Context Learning: Aligning Long-form Generation of Large Language Models via Task-Inherent Attribute Guidelines. - Do Xuan Long; Duong Ngoc Yen; Do Xuan Trong; Anh Tuan Luu; Kenji Kawaguchi; Shafiq Joty; Min-Yen Kan; Nancy F. Chen (ACL (Findings), 2025)

Pruning General Large Language Models into Customized Expert Models. - Yiran Zhao 006; Guizhen Chen; Kenji Kawaguchi; Lidong Bing; Wenxuan Zhang 001 (ACL (Findings), 2025)

Aligning Large Language Models with Human Opinions through Persona Selection and Value-Belief-Norm Reasoning. - Xuan Long Do; Kenji Kawaguchi; Min-Yen Kan; Nancy F. Chen (COLING, 2025)

Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron. - Yiran Zhao 006; Wenxuan Zhang 001; Yuxi Xie; Anirudh Goyal; Kenji Kawaguchi; Michael Shieh (ICLR, 2025)

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. - Seanie Lee; Minsu Kim 004; Lynn Cherif; David Dobre; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (ICLR, 2025)

NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation. - Zhiyuan Liu 001; Yanchen Luo; Han Huang; Enzhi Zhang; Sihang Li 002; Junfeng Fang; Yaorui Shi; Xiang Wang 010; Kenji Kawaguchi; Tat-Seng Chua (ICLR, 2025)

LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs. - Do Xuan Long; Ngoc-Hai Nguyen; Tiviatis Sim; Hieu Dao; Shafiq Joty; Kenji Kawaguchi; Nancy F. Chen; Min-Yen Kan (NAACL (Long Papers), 2025)

Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data. - Haonan Wang; Minbin Huang; Runhui Huang; Lanqing Hong; Hang Xu 004; Tianyang Hu; Xiaodan Liang; Zhenguo Li; Hong Cheng 001; Kenji Kawaguchi (NAACL (Long Papers), 2025)

AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging. - Yiran Zhao 006; Wenxuan Zhang 001; Huiming Wang; Kenji Kawaguchi; Lidong Bing (NAACL (Long Papers), 2025)

DeepOMamba: State-space model for spatio-temporal PDE neural operator learning. - Zheyuan Hu 002; Qianying Cao; Kenji Kawaguchi; George Em Karniadakis (J. Comput. Phys., 2025)

Tensor neural networks for high-dimensional Fokker-Planck equations. - Taorui Wang; Zheyuan Hu 002; Kenji Kawaguchi; Zhongqiang Zhang; George Em Karniadakis (Neural Networks, 2025)

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs. - Zheyuan Hu 002; Zhouhao Yang; Yezhen Wang; George E. Karniadakis; Kenji Kawaguchi (SIAM J. Sci. Comput., 2025)

Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations. - Zheyuan Hu 002; Zhongqiang Zhang; George E. Karniadakis; Kenji Kawaguchi (SIAM J. Sci. Comput., 2025)

When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training. - Haonan Wang; Qian Liu 012; Chao Du; Tongyao Zhu; Cunxiao Du; Kenji Kawaguchi; Tianyu Pang (Trans. Mach. Learn. Res., 2025)

GuardReasoner: Towards Reasoning-based LLM Safeguards. - Yue Liu 008; Hongcheng Gao; Shengfang Zhai; Jun Xia 001; Tianyi Wu; Zhiwei Xue; Yulin Chen; Kenji Kawaguchi; Jiaheng Zhang; Bryan Hooi (CoRR, 2025)

Unnatural Languages Are Not Bugs but Features for LLMs. - Keyu Duan; Yiran Zhao 006; Zhili Feng; Jinjie Ni; Tianyu Pang; Qian Liu 012; Tianle Cai; Longxu Dou; Kenji Kawaguchi; Anirudh Goyal; J. Zico Kolter; Michael Qizhe Shieh (CoRR, 2025)

Rewards Are Enough for Fast Photo-Realistic Text-to-image Generation. - Yihong Luo; Tianyang Hu; Weijian Luo; Kenji Kawaguchi; Jing Tang 004 (CoRR, 2025)

Towards Unified Latent Space for 3D Molecular Latent Diffusion Modeling. - Yanchen Luo; Zhiyuan Liu 001; Yi Zhao; Sihang Li 002; Kenji Kawaguchi; Tat-Seng Chua; Xiang Wang 010 (CoRR, 2025)

Memory-Efficient LLM Training by Various-Grained Low-Rank Projection of Gradients. - Yezhen Wang; Zhouhao Yang; Brian K. Chen; Fanyi Pu; Bo Li; Tianyu Gao; Kenji Kawaguchi (CoRR, 2025)

Fostering Video Reasoning via Next-Event Prediction. - Haonan Wang; Hongfu Liu 002; Xiangyan Liu; Chao Du; Kenji Kawaguchi; Ye Wang 007; Tianyu Pang (CoRR, 2025)

PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations. - Jin Song; Kenji Kawaguchi; Zhenya Yan (CoRR, 2025)

Pruning General Large Language Models into Customized Expert Models. - Yirao Zhao; Guizhen Chen; Kenji Kawaguchi; Lidong Bing; Wenxuan Zhang 001 (CoRR, 2025)

HSG-12M: A Large-Scale Spatial Multigraph Dataset. - Xianquan Yan; Hakan Akgün; Kenji Kawaguchi; N. Duane Loh; Ching Hua Lee (CoRR, 2025)

The Emergence of Abstract Thought in Large Language Models Beyond Any Language. - Yuxin Chen; Yiran Zhao 006; Yang Zhang; An Zhang 003; Kenji Kawaguchi; Shafiq Joty; Junnan Li 001; Tat-Seng Chua; Michael Qizhe Shieh; Wenxuan Zhang 001 (CoRR, 2025)

Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention. - Haonan Wang; Brian K. Chen; Siquan Li; Xinhe Liang; Hwee Kuan Lee; Kenji Kawaguchi; Tianyang Hu (CoRR, 2025)

Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture. - Shuchen Xue; Tianyu Xie 001; Tianyang Hu; Zijin Feng; Jiacheng Sun; Kenji Kawaguchi; Zhenguo Li; Zhi-Ming Ma (CoRR, 2025)

Minimalist Concept Erasure in Generative Models. - Yang Zhang; Er Jin; Yanfei Dong; Yixuan Wu; Philip Torr 001; Ashkan Khakzar; Johannes Stegmaier; Kenji Kawaguchi (CoRR, 2025)

PromptArmor: Simple yet Effective Prompt Injection Defenses. - Tianneng Shi; Kaijie Zhu; Zhun Wang; Yuqi Jia; Will Cai; Weida Liang; Haonan Wang; Hend Alzahrani; Joshua Lu; Kenji Kawaguchi; Basel Alomair; Xuandong Zhao; et al. (CoRR, 2025)

Who's important? - SUnSET: Synergistic Understanding of Stakeholder, Events and Time for Timeline Generation. - Tiviatis Sim; Kaiwen Yang; Shen Xin; Kenji Kawaguchi (CoRR, 2025)

LoReUn: Data Itself Implicitly Provides Cues to Improve Machine Unlearning. - Xiang Li; Qianli Shen; Haonan Wang; Kenji Kawaguchi (CoRR, 2025)