Lai, Chieh-Hsin

32 publications

ICLR 2026 CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow-mAP Models Zheyuan Hu, Chieh-Hsin Lai, Yuki Mitsufuji, Stefano Ermon

ICLR 2026 Concept-TRAK: Understanding How Diffusion Models Learn Concepts Through Concept Attribution Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa, Yuhta Takida, Naoki Murata, Wei-Hsiang Liao, Woosung Choi, Kin Wai Cheuk, Junghyun Koo, Yuki Mitsufuji

ICLR 2026 Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment Bac Nguyen, Yuhta Takida, Naoki Murata, Chieh-Hsin Lai, Toshimitsu Uesaka, Stefano Ermon, Yuki Mitsufuji

ICLR 2026 Improving Classifier-Free Guidance in Masked Diffusion: Low-Dim Theoretical Insights with High-Dim Impact Kevin Rojas, Ye He, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji, Molei Tao

ICLR 2026 SONA: Learning Conditional, Unconditional, and Matching-Aware Discriminator Yuhta Takida, Satoshi Hayakawa, Takashi Shibuya, Masaaki Imaizumi, Naoki Murata, Bac Nguyen, Toshimitsu Uesaka, Chieh-Hsin Lai, Yuki Mitsufuji

ICLRW 2025 Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space Yangming Li, Chieh-Hsin Lai, Carola-Bibiane Schönlieb, Yuki Mitsufuji, Stefano Ermon

ICLRW 2025 Consistency Training with Physical Constraints Che-Chia Chang, Chen-Yang Dai, Te-Sheng Lin, Ming-Chih Lai, Chieh-Hsin Lai

TMLR 2025 G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Bac Nguyen, Stefano Ermon, Yuki Mitsufuji

ICLR 2025 HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Takashi Shibuya, Wei-Hsiang Liao, Shao-Hua Sun, Yuki Mitsufuji

ICLRW 2025 Improving Vector-Quantized Image Modeling with Latent Consistency-Matching Diffusion Bac Nguyen, Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Stefano Ermon, Yuki Mitsufuji

ICLR 2025 Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa, Yuhta Takida, Yuki Mitsufuji

TMLR 2025 Music Foundation Model as Generic Booster for Music Downstream Tasks Wei-Hsiang Liao, Yuhta Takida, Yukara Ikemiya, Zhi Zhong, Chieh-Hsin Lai, Giorgio Fabbro, Kazuki Shimada, Keisuke Toyama, Kin Wai Cheuk, Marco A. Martínez-Ramírez, Shusuke Takahashi, Stefan Uhlich, Taketo Akama, Woosung Choi, Yuichiro Koyama, Yuki Mitsufuji

ICLR 2025 SoundCTM: Unifying Score-Based and Consistency Models for Full-Band Text-to-Sound Generation Koichi Saito, Dongjun Kim, Takashi Shibuya, Chieh-Hsin Lai, Zhi Zhong, Yuhta Takida, Yuki Mitsufuji

ICLRW 2025 Training Consistency Models with Variational Noise Coupling Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji

ICML 2025 VCT: Training Consistency Models with Variational Noise Coupling Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji

ICLR 2025 Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida, Chieh-Hsin Lai, Naoki Murata, Yuki Mitsufuji

ICLR 2024 Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon

NeurIPSW 2024 Disentangling Multi-Instrument Music Audio for Source-Level Pitch and Timbre Manipulation Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi, Wei-Hsiang Liao, Keisuke Toyama, Toshimitsu Uesaka, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Simon Dixon, Yuki Mitsufuji

NeurIPS 2024 GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping Junyoung Seo, Kazumi Fukuda, Takashi Shibuya, Takuya Narihira, Naoki Murata, Shoukang Hu, Chieh-Hsin Lai, Seungryong Kim, Yuki Mitsufuji

TMLR 2024 HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes Yuhta Takida, Yukara Ikemiya, Takashi Shibuya, Kazuki Shimada, Woosung Choi, Chieh-Hsin Lai, Naoki Murata, Toshimitsu Uesaka, Kengo Uchida, Wei-Hsiang Liao, Yuki Mitsufuji

ICLR 2024 Manifold Preserving Guided Diffusion Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon

NeurIPS 2024 PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICLR 2024 SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji

NeurIPSW 2024 SoundCTM: Uniting Score-Based and Consistency Models for Text-to-Sound Generation Koichi Saito, Dongjun Kim, Takashi Shibuya, Chieh-Hsin Lai, Zhi Zhong, Yuhta Takida, Yuki Mitsufuji

ICML 2023 FP-Diffusion: Improving Score-Based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICML 2023 GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration Naoki Murata, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICMLW 2023 On the Equivalence of Consistency-Type Models: Consistency Models, Consistent Diffusion Models, and Fokker-Planck Regularization Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji, Stefano Ermon

AISTATS 2023 Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

NeurIPSW 2022 Regularizing Score-Based Models with Score Fokker-Planck Equations Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICML 2022 SQ-VAE: Variational Bayes on Discrete Representation with Self-Annealed Stochastic Quantization Yuhta Takida, Takashi Shibuya, Weihsiang Liao, Chieh-Hsin Lai, Junki Ohmura, Toshimitsu Uesaka, Naoki Murata, Shusuke Takahashi, Toshiyuki Kumakura, Yuki Mitsufuji

ICLR 2020 Robust Subspace Recovery Layer for Unsupervised Anomaly Detection Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

NeurIPSW 2020 Unlocking Inverse Problems Using Deep Learning: Breaking Symmetries in Phase Retrieval Kshitij Tayal, Chieh-Hsin Lai, Raunak Manekar, Zhong Zhuang, Vipin Kumar, Ju Sun