Asymmetric fourier descriptor of non-closed segments. - Jian-Jiun Ding; Wei-Lun Chao; Jiun-De Huang; Cheng-Jin Kuo (ICIP, 2010)

Coarse-to-fine temporal optimization for video retargeting based on seam carving. - Wei-Lun Chao; Hsiao-Hang Su; Shao-Yi Chien; Winston H. Hsu; Jian-Jiun Ding (ICME, 2011)

Muscle injury determination by image segmentation. - Jian-Jiun Ding; Yu-Hsiang Wang; Lee-Lin Hu; Wei-Lun Chao; Yio-Wha Shau (VCIP, 2011)

Facial age estimation based on label-sensitive learning and age-specific local regression. - Wei-Lun Chao; Jun-Zuo Liu; Jian-Jiun Ding (ICASSP, 2012)

Facial expression recognition using expression-specific local binary patterns and layer denoising mechanism. - Wei-Lun Chao; Jun-Zuo Liu; Jian-Jiun Ding; Po-Hung Wu (ICICS, 2013)

Facial age estimation based on label-sensitive learning and age-oriented regression. - Wei-Lun Chao; Jun-Zuo Liu; Jian-Jiun Ding (Pattern Recognit., 2013)

Diverse Sequential Subset Selection for Supervised Video Summarization. - Boqing Gong; Wei-Lun Chao; Kristen Grauman; Fei Sha (NIPS, 2014)

Exponential Integration for Hamiltonian Monte Carlo. - Wei-Lun Chao; Justin Solomon 001; Dominik L. Michels; Fei Sha (ICML, 2015)

Large-Margin Determinantal Point Processes. - Wei-Lun Chao; Boqing Gong; Kristen Grauman; Fei Sha (UAI, 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 (Signal Process., 2015)

Synthesized Classifiers for Zero-Shot Learning. - Soravit Changpinyo; Wei-Lun Chao; Boqing Gong; Fei Sha (CVPR, 2016)

Summary Transfer: Exemplar-Based Subset Selection for Video Summarization. - Ke Zhang 028; Wei-Lun Chao; Fei Sha; Kristen Grauman (CVPR, 2016)

An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild. - Wei-Lun Chao; Soravit Changpinyo; Boqing Gong; Fei Sha (ECCV (2), 2016)

Video Summarization with Long Short-Term Memory. - Ke Zhang 028; Wei-Lun Chao; Fei Sha; Kristen Grauman (ECCV (7), 2016)

Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning. - Soravit Changpinyo; Wei-Lun Chao; Fei Sha (ICCV, 2017)

Cross-Dataset Adaptation for Visual Question Answering. - Wei-Lun Chao; Hexiang Hu; Fei Sha (CVPR, 2018)

Learning Answer Embeddings for Visual Question Answering. - Hexiang Hu; Wei-Lun Chao; Fei Sha (CVPR, 2018)

Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. - Wei-Lun Chao; Hexiang Hu; Fei Sha (NAACL-HLT, 2018)

An Empirical Study on Leveraging Scene Graphs for Visual Question Answering. - Cheng Zhang 014; Wei-Lun Chao; Dong Xuan (BMVC, 2019)

Vision-only 3D Tracking for Self-Driving Cars. - Carlos Diaz-Ruiz; Yan Wang 051; Wei-Lun Chao; Kilian Q. Weinberger; Mark E. Campbell (CASE, 2019)

Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. - Yan Wang 051; Wei-Lun Chao; Divyansh Garg; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (CVPR, 2019)

A New Defense Against Adversarial Images: Turning a Weakness into a Strength. - Shengyuan Hu 001; Tao Yu; Chuan Guo 001; Wei-Lun Chao; Kilian Q. Weinberger (NeurIPS, 2019)

An Empirical Study of Person Re-Identification with Attributes. - Vikram Shree; Wei-Lun Chao; Mark E. Campbell (RO-MAN, 2019)

SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. - Yan Wang 051; Wei-Lun Chao; Kilian Q. Weinberger; Laurens van der Maaten (CoRR, 2019)

LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. - Brian H. Wang; Wei-Lun Chao; Yan Wang 051; Bharath Hariharan; Kilian Q. Weinberger; Mark Campbell 001 (IEEE Robotics Autom. Lett., 2019)

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. - Rui Qian; Divyansh Garg; Yan Wang 051; Yurong You; Serge J. Belongie; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger; Wei-Lun Chao (CVPR, 2020)

Train in Germany, Test in the USA: Making 3D Object Detectors Generalize. - Yan Wang 051; Xiangyu Chen 007; Yurong You; Li Erran Li; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger; Wei-Lun Chao (CVPR, 2020)

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. - Yurong You; Yan Wang 051; Wei-Lun Chao; Divyansh Garg; Geoff Pleiss; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (ICLR, 2020)

Wasserstein Distances for Stereo Disparity Estimation. - Divyansh Garg; Yan Wang 051; Bharath Hariharan; Mark Campbell 001; Kilian Q. Weinberger; Wei-Lun Chao (NeurIPS, 2020)

Visual Question Answering on 360° Images. - Shih-Han Chou; Wei-Lun Chao; Wei-Sheng Lai; Min Sun 001; Ming-Hsuan Yang 001 (WACV, 2020)

Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning. - Han-Jia Ye; Hong-You Chen; De-Chuan Zhan; Wei-Lun Chao (CoRR, 2020)

Revisiting Meta-Learning as Supervised Learning. - Wei-Lun Chao; Han-Jia Ye; De-Chuan Zhan; Mark E. Campbell; Kilian Q. Weinberger (CoRR, 2020)

MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. - Luyu Yang; Yan Wang 051; Mingfei Gao; Abhinav Shrivastava; Kilian Q. Weinberger; Wei-Lun Chao; Ser-Nam Lim (CoRR, 2020)

FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning. - Hong-You Chen; Wei-Lun Chao (CoRR, 2020)

Classifier and Exemplar Synthesis for Zero-Shot Learning. - Soravit Changpinyo; Wei-Lun Chao; Boqing Gong; Fei Sha (Int. J. Comput. Vis., 2020)

Interactive Natural Language-Based Person Search. - Vikram Shree; Wei-Lun Chao; Mark Campbell 001 (IEEE Robotics Autom. Lett., 2020)

Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering. - Jihyung Kil; Cheng Zhang 014; Dong Xuan; Wei-Lun Chao (EMNLP (1), 2021)

Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. - Luyu Yang; Yan Wang 051; Mingfei Gao; Abhinav Shrivastava; Kilian Q. Weinberger; Wei-Lun Chao; Ser-Nam Lim (ICCV, 2021)

Procrustean Training for Imbalanced Deep Learning. - Han-Jia Ye; De-Chuan Zhan; Wei-Lun Chao (ICCV, 2021)

MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. - Cheng Zhang 014; Tai-Yu Pan; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (ICCV, 2021)

FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning. - Hong-You Chen; Wei-Lun Chao (ICLR, 2021)

Revisiting Document Representations for Large-Scale Zero-Shot Learning. - Jihyung Kil; Wei-Lun Chao (NAACL-HLT, 2021)

Gradual Domain Adaptation without Indexed Intermediate Domains. - Hong-You Chen; Wei-Lun Chao (NeurIPS, 2021)

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation. - Tai-Yu Pan; Cheng Zhang 014; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (NeurIPS, 2021)

A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. - Cheng Zhang 014; Tai-Yu Pan; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (CoRR, 2021)

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection. - Yurong You; Carlos Andres Diaz-Ruiz; Yan Wang 051; Wei-Lun Chao; Bharath Hariharan; Mark Campbell 001; Kilian Q. Weinberger (CoRR, 2021)

On Bridging Generic and Personalized Federated Learning. - Hong-You Chen; Wei-Lun Chao (CoRR, 2021)

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans. - Tai-Hsien Wu; Chunfeng Lian; Sanghee Lee; Matthew Pastewait; Christian Piers; Jie Liu; Fang Wang; Li Wang 026; Christina Jackson; Wei-Lun Chao; Dinggang Shen; Ching-Chang Ko (CoRR, 2021)

Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions. - Carlos Andres Diaz-Ruiz; Youya Xia; Yurong You; Jose Nino; Junan Chen; Josephine Monica; Xiangyu Chen 007; Katie Luo; Yan Wang 051; Marc Emond; Wei-Lun Chao; Bharath Hariharan; et al. (CVPR, 2022)

One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones. - Chan Hee Song; Jihyung Kil; Tai-Yu Pan; Brian M. Sadler; Wei-Lun Chao; Yu Su 001 (CVPR, 2022)

Learning to Detect Mobile Objects from LiDAR Scans Without Labels. - Yurong You; Katie Luo; Cheng Perng Phoo; Wei-Lun Chao; Wen Sun 002; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (CVPR, 2022)

Learning with Free Object Segments for Long-Tailed Instance Segmentation. - Cheng Zhang 014; Tai-Yu Pan; Tianle Chen; Jike Zhong; Wenjin Fu; Wei-Lun Chao (ECCV (10), 2022)

On Bridging Generic and Personalized Federated Learning for Image Classification. - Hong-You Chen; Wei-Lun Chao (ICLR, 2022)

How to Train Your MAML to Excel in Few-Shot Classification. - Han-Jia Ye; Wei-Lun Chao (ICLR, 2022)

Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. - Yurong You; Katie Z. Luo; Xiangyu Chen 007; Junan Chen; Wei-Lun Chao; Wen Sun 002; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (ICLR, 2022)

Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling. - Josephine Monica; Wei-Lun Chao; Mark E. Campbell (ICRA, 2022)

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection in Self-Driving Cars. - Yurong You; Carlos Andres Diaz-Ruiz; Yan Wang 051; Wei-Lun Chao; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (ICRA, 2022)

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. - Yurong You; Cheng Perng Phoo; Katie Luo; Travis Zhang; Wei-Lun Chao; Bharath Hariharan; Mark Campbell 001; Kilian Q. Weinberger (NeurIPS, 2022)

On Pre-Training for Federated Learning. - Hong-You Chen; Cheng-Hao Tu 001; Ziwei Li; Han-Wei Shen; Wei-Lun Chao (CoRR, 2022)

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans. - Tai-Hsien Wu; Chunfeng Lian; Sanghee Lee; Matthew Pastewait; Christian Piers; Jie Liu; Fan Wang 023; Li Wang 026; Chiung-Ying Chiu; Wenchi Wang; Christina Jackson; Wei-Lun Chao; et al. (IEEE Trans. Medical Imaging, 2022)

Learning Fractals by Gradient Descent. - Cheng-Hao Tu 001; Hong-You Chen; David Carlyn; Wei-Lun Chao (AAAI, 2023)

Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. - Cheng-Hao Tu 001; Zheda Mai; Wei-Lun Chao (CVPR, 2023)

Train-Once-for-All Personalization. - Hong-You Chen; Yandong Li; Yin Cui; Mingda Zhang; Wei-Lun Chao; Li Zhang 003 (CVPR, 2023)

Towards Open-World Segmentation of Parts. - Tai-Yu Pan; Qing Liu 017; Wei-Lun Chao; Brian L. Price (CVPR, 2023)

FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows. - Yuxiao Qu; Jinmeng Rao; Song Gao 001; Qianheng Zhang; Wei-Lun Chao; Yu Su 001; Michelle Miller 006; Alfonso Morales; Patrick R. Huber (GeoAI@SIGSPATIAL, 2023)

Unified Out-Of-Distribution Detection: A Model-Specific Perspective. - Reza Averly; Wei-Lun Chao (ICCV, 2023)

PreSTU: Pre-Training for Scene-Text Understanding. - Jihyung Kil; Soravit Changpinyo; Xi Chen 071; Hexiang Hu; Sebastian Goodman; Wei-Lun Chao; Radu Soricut (ICCV, 2023)

LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models. - Chan Hee Song; Brian M. Sadler; Jiaman Wu; Wei-Lun Chao; Clayton Washington; Yu Su 001 (ICCV, 2023)

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features. - Travis Zhang; Katie Luo; Cheng Perng Phoo; Yurong You; Wei-Lun Chao; Bharath Hariharan; Mark E. Campbell; Kilian Q. Weinberger (ICCV (Workshops), 2023)

On the Importance and Applicability of Pre-Training for Federated Learning. - Hong-You Chen; Cheng-Hao Tu 001; Ziwei Li; Han-Wei Shen; Wei-Lun Chao (ICLR, 2023)

Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization. - Junan Chen; Josephine Monica; Wei-Lun Chao; Mark E. Campbell (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 E. Campbell (ICRA, 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 M. Dahdul; Yasin Bakis; Henry L. Bart Jr.; Paula M. Mabee; Hilmar Lapp; James P. Balhoff; Caleb Charpentier; et al. (KDD, 2023)

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. - Cheng-Hao Tu 001; Hong-You Chen; Zheda Mai; Jike Zhong; Vardaan Pahuja; Tanya Y. Berger-Wolf; Song Gao 001; Charles V. Stewart; Yu Su 001; Wei-Lun Chao (NeurIPS, 2023)

Making Batch Normalization Great in Federated Deep Learning. - Jike Zhong; Hong-You Chen; Wei-Lun Chao (CoRR, 2023)

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification. - Hong-You Chen; Jike Zhong; Mingda Zhang; Xuhui Jia; Hang Qi; Boqing Gong; Wei-Lun Chao; Li Zhang 003 (CoRR, 2023)

Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation. - Tianle Chen; Zheda Mai; Ruiwen Li; Wei-Lun Chao (CoRR, 2023)

Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment. - Yang Tang; Shuang Song 010; Shengxi Gui; Wei-Lun Chao; Chinmin Cheng; Rongjun Qin (Sensors, 2023)

Visual Analytics on Network Forgetting for Task-Incremental Learning. - Ziwei Li; Jiayi Xu 001; Wei-Lun Chao; Han-Wei Shen (Comput. Graph. Forum, 2023)

Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs. - Vardaan Pahuja; Weidi Luo; Yu Gu 016; Cheng-Hao Tu 001; Hong-You Chen; Tanya Y. Berger-Wolf; Charles V. Stewart; Song Gao 001; Wei-Lun Chao; Yu Su 001 (CIKM, 2024)

Dual-View Visual Contextualization for Web Navigation. - Jihyung Kil; Chan Hee Song; Boyuan Zheng; Xiang Deng 001; Yu Su 001; Wei-Lun Chao (CVPR, 2024)

BioCLIP: A Vision Foundation Model for the Tree of Life. - Samuel Stevens 001; Jiaman Wu; Matthew J. Thompson; Elizabeth G. Campolongo; Chan Hee Song; David Edward Carlyn; Li Dong; Wasila M. Dahdul; Charles V. Stewart; Tanya Y. Berger-Wolf; Wei-Lun Chao; Yu Su 001 (CVPR, 2024)

Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution. - Mridul Khurana; Arka Daw; M. Maruf; Josef C. Uyeda; Wasila M. Dahdul; Caleb Charpentier; Yasin Bakis; Henry L. Bart Jr.; Paula M. Mabee; Hilmar Lapp; James P. Balhoff; Wei-Lun Chao; et al. (ECCV (89), 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 001; Kilian Q. Weinberger; Bharath Hariharan; Wei-Lun Chao (ICLR, 2024)

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis. - Dipanjyoti Paul; Arpita Chowdhury; Xinqi Xiong; Feng-Ju Chang; David Edward Carlyn; Samuel Stevens 001; Kaiya Provost; Anuj Karpatne; Bryan Carstens; Daniel I. Rubenstein; Charles V. Stewart; Tanya Y. Berger-Wolf; et al. (ICLR, 2024)

Better Monocular 3D Detectors with LiDAR from the Past. - Yurong You; Cheng Perng Phoo; Carlos Andres Diaz-Ruiz; Katie Z. Luo; Wei-Lun Chao; Mark E. Campbell; Bharath Hariharan; Kilian Q. Weinberger (ICRA, 2024)

DiffuBox: Refining 3D Object Detection with Point Diffusion. - Xiangyu Chen 007; Zhenzhen Liu; Katie Luo; Siddhartha Datta; Adhitya Polavaram; Yan Wang 051; Yurong You; Boyi Li; Marco Pavone 001; Wei-Lun Chao; Mark E. Campbell; Bharath Hariharan; et al. (NeurIPS, 2024)

MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs. - Jihyung Kil; Zheda Mai; Justin Lee; Arpita Chowdhury; Zihe Wang; Kerrie Cheng; Lemeng Wang; Ye Liu; Wei-Lun Chao (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, 2024)

Fine-Tuning is Fine, if Calibrated. - Zheda Mai; Arpita Chowdhury; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Vardaan Pahuja; Tanya Y. Berger-Wolf; Song Gao 001; Charles V. Stewart; Yu Su 001; Wei-Lun Chao (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; et al. (NeurIPS, 2024)

Bringing Back the Context: Camera Trap Species Identification as Link Prediction on Multimodal Knowledge Graphs. - Vardaan Pahuja; Weidi Luo; Yu Gu 016; Cheng-Hao Tu 001; Hong-You Chen; Tanya Y. Berger-Wolf; Charles V. Stewart; Song Gao 001; Wei-Lun Chao; Yu Su 001 (CoRR, 2024)

Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images. - Kazi Sajeed Mehrab; M. Maruf; Arka Daw; Harish Babu Manogaran; Abhilash Neog; Mridul Khurana; Bahadir Altintas; Yasin Bakis; Elizabeth G. Campolongo; Matthew J. Thompson; Xiaojun Wang; Hilmar Lapp; et al. (CoRR, 2024)

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 (CoRR, 2024)

Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition. - Zheda Mai; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Li Zhang 003; Wei-Lun Chao (CoRR, 2024)

KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models. - Pouyan Navard; Amin Karimi Monsefi; Mengxi Zhou; Wei-Lun Chao; Alper Yilmaz; Rajiv Ramnath (CoRR, 2024)

Jigsaw Game: Federated Clustering. - Jinxuan Xu; Hong-You Chen; Wei-Lun Chao; Yuqian Zhang (Trans. Mach. Learn. Res., 2024)

Few-Shot Learning With a Strong Teacher. - Han-Jia Ye; Lu Ming; De-Chuan Zhan; Wei-Lun Chao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

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 I. Rubenstein; Charles V. Stewart; Anuj Karpatne; Tanya Y. Berger-Wolf; Yu Su 001; et al. (CVPR, 2025)

Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition. - Zheda Mai; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Quang-Huy Nguyen; Li Zhang 003; 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; et al. (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 E. Campbell; Kilian Q. Weinberger; Bharath Hariharan; 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 Y. Berger-Wolf; Yu Su 001; Wei-Lun Chao (CVPR, 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 C. Uyeda; Wasila M. Dahdul; Matthew J. Thompson; Elizabeth G. Campolongo; Kaiya L. Provost; Wei-Lun Chao; Tanya Y. Berger-Wolf; et al. (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 (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 (ICLR, 2025)

Learning 3D Perception from Others' Predictions. - Jinsu Yoo; Zhenyang Feng; Tai-Yu Pan; Yihong Sun; Cheng Perng Phoo; Xiangyu Chen 007; Mark E. Campbell; Kilian Q. Weinberger; Bharath Hariharan; Wei-Lun Chao (ICLR, 2025)

OmniMesh: Addressing Findability Challenges in Distributed Nature Data Repositories. - Arnab Nandi 001; Wei-Lun Chao; Rongjun Qin; Carl Boettiger; Hilmar Lapp; Tanya Y. Berger-Wolf (SSDBM, 2025)

Static Segmentation by Tracking: A Frustratingly Label-Efficient Approach to Fine-Grained Segmentation. - Zhenyang Feng; Zihe Wang; Saul Ibaven Bueno; Tomasz Frelek; Advikaa Ramesh; Jingyan Bai; Lemeng Wang; Zanming Huang; Jianyang Gu; Jinsu Yoo; Tai-Yu Pan; Arpita Chowdhury; et al. (CoRR, 2025)

Prompt-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis. - Arpita Chowdhury; Dipanjyoti Paul; Zheda Mai; Jianyang Gu; Ziheng Zhang; Kazi Sajeed Mehrab; Elizabeth G. Campolongo; Daniel I. Rubenstein; Charles V. Stewart; Anuj Karpatne; Tanya Y. Berger-Wolf; Yu Su 001; et al. (CoRR, 2025)

Sparse Autoencoders for Scientifically Rigorous Interpretation of Vision Models. - Samuel Stevens 001; Wei-Lun Chao; Tanya Y. Berger-Wolf; Yu Su 001 (CoRR, 2025)

Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration. - Katie Z. Luo; Minh-Quan Dao; Zhenzhen Liu; Mark E. Campbell; Wei-Lun Chao; Kilian Q. Weinberger; Ezio Malis; Vincent Frémont; Bharath Hariharan; Mao Shan; Stewart Worrall 002; Julie Stephany Berrio Perez (CoRR, 2025)

A Closer Look at TabPFN v2: Strength, Limitation, and Extension. - Han-Jia Ye; Si-Yang Liu; Wei-Lun Chao (CoRR, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

Federated Inverse Probability Treatment Weighting for Individual Treatment Effect Estimation. - Changchang Yin; Hong-You Chen; Wei-Lun Chao; Ping Zhang 016 (CoRR, 2025)

Revisiting semi-supervised learning in the era of foundation models. - Ping Zhang 016; Zheda Mai; Quang-Huy Nguyen; Wei-Lun Chao (CoRR, 2025)

BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning. - Jianyang Gu; Samuel Stevens 001; Elizabeth G. Campolongo; Matthew J. Thompson; Net Zhang; Jiaman Wu; Andrei Kopanev; Zheda Mai; Alexander E. White; James P. Balhoff; Wasila M. Dahdul; Daniel I. Rubenstein; et al. (CoRR, 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 014 (CoRR, 2025)

High-Fidelity Scientific Simulation Surrogates via Adaptive Implicit Neural Representations. - Ziwei Li; Yuhan Duan; Tianyu Xiong; Yi-Tang Chen; Wei-Lun Chao; Han-Wei Shen (CoRR, 2025)

AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models. - Zheda Mai; Arpita Chowdhury; Zihe Wang; Sooyoung Jeon; Lemeng Wang; Jiacheng Hou; Jihyung Kil; Wei-Lun Chao (CoRR, 2025)

A Rigorous Behavior Assessment of CNNs Using a Data-Domain Sampling Regime. - Shuning Jiang; Wei-Lun Chao; Daniel Haehn; Hanspeter Pfister; Jian Chen (CoRR, 2025)

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective. - Jinsu Yoo; Sooyoung Jeon; Zanming Huang; Tai-Yu Pan; Wei-Lun Chao (CoRR, 2025)