Please see my Google scholar page here.
Selected Publications
ML (30): 15 NeurIPS/NIPS, 12 ICLR, 1 ICML, 1 UAI, 1 KDD
Vision (36): 20 CVPR, 9 ICCV, 4 ECCV, 1 PAMI, 1 IJCV, 1 PR
NLP (3): 2 NAACL, 1 EMNLP
Robotics (7): 2 RA-L, 5 ICRA
AI (1): 1 AAAI
Perception for Autonomous Driving
ICCV 2025. "Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration." Katie Z Luo, Minh-Quan Dao, Zhenzhen Liu, Mark Campbell, Wei-Lun Chao, Kilian Q Weinberger, Ezio Malis, FREMONT Vincent, Bharath Hariharan, Mao Shan, Stewart Worrall, Julie Stephany Berrio Perez.
CVPR 2025. "Transfer Your Perspective: Controllable 3D Generation from Any Viewpoint in a Driving Scene." Tai-Yu Pan, Sooyoung Jeon, Mengdi Fan, Jinsu Yoo, Zhenyang Feng, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao.
ICLR 2025. "Learning 3D Perception from Others' Predictions." Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan, Yihong Sun, Cheng Perng Phoo, Xiangyu Chen, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao.
NeurIPS 2024. "DiffuBox: Refining 3D Object Detection with Point Diffusion." Xiangyu Chen, Zhenzhen Liu, Katie Z Luo, Siddhartha Datta, Adhitya Polavaram, Yan Wang, Yurong You, Boyi Li, Marco Pavone, Wei-Lun Chao, Mark Campbell, Bharath Hariharan, Kilian Q. Weinberger.
ICLR 2024. "Pre-Training LiDAR-Based 3D Object Detectors Through Colorization." Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z Luo, Yurong You, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao.
ICRA 2024. "Better Monocular 3D Detectors with LiDAR from the Past." Yurong You, Cheng Perng Phoo, Carlos Diaz-Ruiz, Katie Luo, Wei-Lun Chao, Mark Campbell, Bharath Hariharan, Kilian Weinberger
ICRA 2023. "Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs." Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell
ICRA 2023. "Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization." Junan Chen, Josephine Monica, Wei-Lun Chao, Mark Campbell
CVPR 2022. "Learning to Detect Mobile Objects from LiDAR Scans Without Labels." Yurong You, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, and Kilian Weinberger. [link, pdf, suppl, code]
CVPR 2022. "Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions." Carlos Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Weinberger, and Mark Campbell. [link, pdf, suppl, data]
ICLR 2022. "Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception." Yurong You, Katie Z Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger. [link, pdf, code]
ICRA 2022. "Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling" Josephine Monica, Wei-Lun Chao, and Mark Campbell. [link, pdf]
NeurIPS 2020. "Wasserstein Distances for Stereo Disparity Estimation." Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
CVPR 2020. "End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection." Rui Qian*, Divyansh Garg*, Yan Wang, Yurong You, Serge Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
ICLR 2020. "Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving." Yurong You*, Yan Wang*, Wei-Lun Chao*, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger.
CVPR 2019. "Pseudo-LiDAR from visual depth estimation: bridging the gap in 3D object detection for autonomous driving." Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger.
RA-L 2019. "LDLS: 3D Object Segmentation through Label Diffusion from 2D Images." Brian Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, and Mark Campbell.
Learning with Imperfect Data
Domain Adaptation
NeurIPS 2024. "Fine-Tuning is Fine, if Calibrated." Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao.
NeurIPS 2023. "Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data." Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao.
NeurIPS 2022. "Unsupervised Adaptation from Repeated Traversals for Autonomous Driving." Yurong You, Cheng Perng Phoo, Katie Z Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger. [link, pdf, suppl]
ICRA 2022. "Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection." Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger. [link, pdf]
NeurIPS 2021. "Gradual Domain Adaptation without Indexed Intermediate Domains." Hong-You Chen and Wei-Lun Chao. [link, pdf, suppl]
ICCV 2021. "Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation." Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, and Ser-Nam Lim.
CVPR 2020. "Train in Germany, Test in the USA: Making 3D Object Detectors Generalize." Yan Wang*, Xiangyu Chen*, Yurong You*, Li Erran Li, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
CVPR 2018. "Cross-dataset adaptation for visual question answering." Wei-Lun Chao*, Hexiang Hu*, and Fei Sha.
Imbalanced Learning
ECCV 2022. "Learning with Free Object Segments for Long-Tailed Instance Segmentation." Cheng Zhang, Tai-Yu Pan, Tianle Chen, Jike Zhong, Wenjin Fu, and Wei-Lun Chao. [link, pdf, suppl]
NeurIPS 2021. "On Model Calibration for Long-Tailed Object Detection and Instance Segmentation." Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, and Wei-Lun Chao. [link, pdf, suppl]
ICCV 2021. "Procrustean Training for Imbalanced Deep Learning." Han-Jia Ye, De-Chuan Zhan, and Wei-Lun Chao.
ICCV 2021. "MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection." Cheng Zhang, Tai-Yu Pan, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, and Wei-Lun Chao.
arXiv 2020. "Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning." Han-Jia Ye, Hong-You Chen, De-Chuan Zhan, and Wei-Lun Chao.
Meta-Learning and Few-Shot Learning
CVPR 2025. "Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition." Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Quang-Huy Nguyen, Li Zhang, Wei-Lun Chao.
CVPR 2023. "Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning." Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao.
ICLR 2022. "How to Train Your MAML to Excel in Few-Shot Classification." Han-Jia Ye and Wei-Lun Chao. [link, pdf, code]
PAMI 2022. "Few-Shot Learning with a Strong Teacher." Han-Jia Ye, Lu Ming, De-Chuan Zhan, and Wei-Lun Chao. [link, pdf, code]
arXiv 2020. "Revisiting Meta-Learning as Supervised Learning." Wei-Lun Chao*, Han-Jia Ye*, De-Chuan Zhan, Mark Campbell, and Kilian Q. Weinberger.
arXiv 2019 (cited > 200 times). "SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning." Yan Wang, Wei-Lun Chao, Kilian Q Weinberger, and Laurens van der Maaten.
Zero-Shot Learning
CVPR 2023. "Towards Open-World Segmentation of Parts." Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian L. Price
NAACL 2021. "Revisiting Document Representations for Large-Scale Zero-Shot Learning." Jihyung Kil and Wei-Lun Chao.
IJCV 2020. "Classifier and Exemplar Synthesis for Zero-Shot Learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, and Fei Sha.
ICCV 2017. "Predicting visual exemplars of unseen classes for zero-shot learning." Soravit Changpinyo, Wei-Lun Chao, and Fei Sha.
ECCV 2016. "An empirical study and analysis of generalized zero-shot learning for object recognition in the wild." Wei-Lun Chao*, Soravit Changpinyo*, Boqing Gong, and Fei Sha.
CVPR 2016. "Synthesized classifiers for zero-shot learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, and Fei Sha.
Federated Learning
NeurIPS 2024. "FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction." Ziwei Li, Xiaoqi Wang, Hong-You Chen, Han Wei Shen, Wei-Lun Chao.
NeurIPS 2023-Workshop. "Making Batch Normalization Great in Federated Deep Learning." Jike Zhong, Hong-You Chen, Wei-Lun Chao.
ICLR 2023. "On the Importance and Applicability of Pre-Training for Federated Learning." Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, Wei-Lun Chao.
NeurIPS 2022-Workshop. "Understanding Federated Learning through Loss Landscape Visualizations: A Pilot Study." Ziwei Li, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao.
ICLR 2022. "On Bridging Generic and Personalized Federated Learning for Image Classification." Hong-You Chen and Wei-Lun Chao. [link, pdf]
ICLR 2021. "FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning." Hong-You Chen and Wei-Lun Chao. (A preliminary version won the best student paper in SpicyFL 2020: NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning)
Personalization
CVPR 2023. "Train-Once-for-All Personalization." Hong-You Chen, Yandong Li, Yin Cui, Mingda Zhang, Wei-Lun Chao, Li Zhang
OOD Detection
ICCV 2023. "Unified Out-Of-Distribution Detection: A Model-Specific Perspective." Muhammad Reza Averly, Wei-Lun Chao.
Weakly-Supervised Learning, Semi-Supervised Learning, and Self-Supervised Learning
NeurIPS 2025. "Revisiting semi-supervised learning in the era of foundation models." Ping Zhang, Zheda Mai, Quang-Huy Nguyen, Wei-Lun Chao.
ICLR 2025. "Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning." Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi, Ser-Nam Lim, Wei-Lun Chao, Rajiv Ramnath.
NeurIPS 2023-Workshop. "Segment Anything Model (SAM) Enhances PseudoLabels for Weakly Supervised Semantic Segmentation." Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao.
CV/ML for Imageomics (CV/ML meets Biology)
NeurIPS 2025. "BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning." Jianyang Gu, Samuel Stevens, Elizabeth G Campolongo, Matthew J Thompson, Net Zhang, Jiaman Wu, Andrei Kopanev, Zheda Mai, Alexander E. White, James Balhoff, Wasila Dahdul, Daniel Rubenstein, Hilmar Lapp, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su.
ICCV 2025. "TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation." Amin Karimi Monsefi, Mridul Khurana, Rajiv Ramnath, Anuj Karpatne, Wei-Lun Chao, Cheng Zhang.
CVPR 2025-CV4Animals Workshop (oral). "Static Segmentation by Tracking: A Label-Efficient Approach for Fine-Grained Specimen Image Segmentation." Zhenyang Feng, Zihe Wang, Jianyang Gu, Saul Ibaven Bueno, Tomasz Frelek, Advikaa Ramesh, Jingyan Bai, Lemeng Wang, Zanming Huang, Jinsu Yoo, Tai-Yu Pan, Arpita Chowdhury, Michelle Ramirez, Elizabeth G Campolongo, Matthew J Thompson, Christopher G. Lawrence, Sydne Record, Neil Rosser, Anuj Karpatne, Daniel Rubenstein, Hilmar Lapp, Charles V. Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao.
CVPR 2025. "Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis." Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G Campolongo, Daniel Rubenstein, Charles V. Stewart, Anuj Karpatne, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao.
CVPR 2025. "Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation." Ziheng Zhang, Jianyang Gu, Arpita Chowdhury, Zheda Mai, David Carlyn, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao.
CVPR 2025. "Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images." Kazi Sajeed Mehrab, M. Maruf, Arka Daw, Abhilash Neog, Harish Babu Manogaran, Mridul Khurana, Zhenyang Feng, Bahadir Altintas, Yasin Bakis, Elizabeth G Campolongo, Matthew J Thompson, Xiaojun Wang, Hilmar Lapp, Tanya Berger-Wolf, Paula Mabee, Henry Bart, Wei-Lun Chao, Wasila M Dahdul, Anuj Karpatne.
ICLR 2025. "What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits." Harish Babu Manogaran, M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Caleb Patrick Charpentier, Josef Uyeda, Wasila M Dahdul, Matthew J Thompson, Elizabeth G Campolongo, Kaiya L Provost, Wei-Lun Chao, Tanya Berger-Wolf, Paula Mabee, Hilmar Lapp, Anuj Karpatne
NeurIPS 2024. "VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images." M Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James P Balhoff, Yasin Bakis, Bahadir Altintas, Matthew J Thompson, Elizabeth G Campolongo, Josef C Uyeda, Hilmar Lapp, Henry L Bart, Paula M Mabee, Yu Su, Wei-Lun Chao, Charles Stewart, Tanya Berger-Wolf, Wasila Dahdul, Anuj Karpatne.
CIKM 2024. "Bringing back the context: Camera trap species identification as link prediction on multimodal knowledge graphs." Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Berger-Wolf, Charles Stewart, Song Gao, Wei-Lun Chao, Yu Su.
ECCV 2024. "Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution." Mridul Khurana, Arka Daw, M. Maruf, Josef Uyeda, Wasila Dahdul, Caleb Charpentier, Yasin Bakış, Henry L. Bart Jr., Paula Mabee, Hilmar Lapp, James Balhoff, Wei-Lun Chao, Charles Stewart, Tanya Berger-Wolf, Anuj Karpatne.
ICLR 2024. "A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis." Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao.
CVPR 2024. "BioCLIP: A Vision Foundation Model for the Tree of Life." Samuel Stevens, Jiaman Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su
KDD 2023. "Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks." Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C Uyeda, Meghan A Balk, Wasila Dahdul, Yasin Bakış, Henry L Bart Jr, Paula M Mabee, Hilmar Lapp, James P Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V Stewart, Daniel I Rubenstein, Tanya Berger-Wolf, Anuj Karpatne
Vision and Language
NeurIPS 2024. "MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs." Jihyung Kil, Zheda Mai, Justin Lee, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Arpita Chowdhury, Wei-Lun Chao.
CVPR 2024. "Dual-View Visual Contextualization for Web Navigation." Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao.
ICCV 2023. "LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models." Chan Hee Song, Jiaman Wu, Clayton Washington, Brian Sadler, Wei-Lun Chao, Yu Su.
ICCV 2023. "PreSTU: Pre-Training for Scene-Text Understanding." Jihyung Kil, Soravit Changpinyo, Xi Chen, Hexiang Hu, Sebastian Goodman, Wei-Lun Chao, Radu Soricut
CVPR 2022. "One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones." Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian Sadler, Wei-Lun Chao, and Yu Su. [link, pdf, suppl]
EMNLP 2021. "Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering." Jihyung Kil, Cheng Zhang, Dong Xuan, and Wei-Lun Chao.
WACV 2020. "Visual Question Answering on 360 Images." Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai, Min Sun, and Ming-Hsuan Yang.
RA-L 2020. "Interactive Natural Language-based Person Search." Vikram Shree, Wei-Lun Chao, and Mark Campbell.
BMVC, 2019. "An Empirical Study on Leveraging Scene Graphs for Visual Question Answering." Cheng Zhang, Wei-Lun Chao, and Dong Xuan.
CVPR 2018. "Learning answer embeddings for visual question answering." Hexiang Hu*, Wei-Lun Chao*, and Fei Sha.
NAACL 2018. "Being negative but constructively: lessons learnt from creating better visual question answering datasets." Wei-Lun Chao*, Hexiang Hu*, and Fei Sha.
Health Care
Gastrointestinal Endoscopy 2021. "High performance in risk stratification of intraductal papillary mucinous neoplasms by confocal laser endomicroscopy image analysis with convolutional neural networks (with video)." Jorge D. Machicado, Wei-Lun Chao, David E. Carlyn, Tai-Yu Pan, Sarah Poland, Victoria L. Alexander, Tassiana G. Maloof et al.
Video Summarization
ECCV 2016. "Video summarization with long short-term memory." Ke Zhang*, Wei-Lun Chao*, Fei Sha, and Kristen Grauman.
CVPR 2016. "Summary transfer: exemplar-based subset selection for video summarization." Ke Zhang*, Wei-Lun Chao*, Fei Sha, and Kristen Grauman.
UAI 2015. "Large-margin determinantal point processes." Wei-Lun Chao*, Boqing Gong*, Kristen Grauman, and Fei Sha.
NIPS 2014. "Diverse sequential subset selection for supervised video summarization." Boqing Gong*, Wei-Lun Chao*, Kristen Grauman, and Fei Sha.
Others
NeurIPS 2025. "A Closer Look at TabPFN v2: Understanding Its Strengths and Extending Its Capabilities." Han-Jia Ye, Si-Yang Liu, Wei-Lun Chao.
ICLR 2025. "Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later." Han-Jia Ye, Huai-Hong Yin, De-Chuan Zhan, Wei-Lun Chao.
AAAI 2023. "Learning Fractals by Gradient Descent." Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao.
NeurIPS 2019. "A New Defense Against Adversarial Images: Turning a Weakness into a Strength." Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, and Kilian Q. Weinberger.
ICML 2015. "Exponential Integration for Hamiltonian Monte Carlo." Wei-Lun Chao, Justin Solomon, Dominik Michels, and Fei Sha.
Signal Processing 2015. "Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection." Wei-Lun Chao, Jian-Jiun Ding, Jun-Zuo Liu.
Pattern Recognition 2013. "Facial age estimation based on label-sensitive learning and age-oriented regression." Wei-Lun Chao, Jun-Zuo Liu, and Jian-Jiun Ding.