A General Algorithm for Approximate Inference and Its Application to Hybrid Bayes Nets. - Daphne Koller; Uri Lerner; Dragomir Anguelov (UAI, 1999)

Mining the stock market (extended abstract): which measure is best? - Martin Gavrilov; Dragomir Anguelov; Piotr Indyk; Rajeev Motwani 001 (KDD, 2000)

Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots. - Dragomir Anguelov; Rahul Biswas; Daphne Koller; Benson Limketkai; Sebastian Thrun (UAI, 2002)

Detecting and Modeling Doors with Mobile Robots. - Dragomir Anguelov; Daphne Koller; Evan Parker; Sebastian Thrun (ICRA, 2004)

The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces. - Dragomir Anguelov; Praveen Srinivasan; Hoi-Cheung Pang; Daphne Koller; Sebastian Thrun; James Davis 001 (NIPS, 2004)

Recovering Articulated Object Models from 3D Range Data. - Dragomir Anguelov; Daphne Koller; Hoi-Cheung Pang; Praveen Srinivasan; Sebastian Thrun (UAI, 2004)

Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. - Dragomir Anguelov; Benjamin Taskar; Vassil Chatalbashev; Daphne Koller; Dinkar Gupta; Geremy Heitz; Andrew Y. Ng (CVPR (2), 2005)

SCAPE: shape completion and animation of people. - Dragomir Anguelov; Praveen Srinivasan; Daphne Koller; Sebastian Thrun; Jim Rodgers; James Davis 001 (ACM Trans. Graph., 2005)

Object Pose Detection in Range Scan Data. - Jim Rodgers; Dragomir Anguelov; Hoi-Cheung Pang; Daphne Koller (CVPR (2), 2006)

Learning models of shape from 3D range data. - Dragomir Anguelov (2006)

Contextual Identity Recognition in Personal Photo Albums. - Dragomir Anguelov; Kuang-chih Lee; Salih Burak Göktürk; Baris Sumengen (CVPR, 2007)

Markov random field models for hair and face segmentation. - Kuang-chih Lee; Dragomir Anguelov; Baris Sumengen; Salih Burak Göktürk (FG, 2008)

High quality pose estimation by aligning multiple scans to a latent map. - Qi-Xing Huang; Dragomir Anguelov (ICRA, 2010)

Hybrid hessians for flexible optimization of pose graphs. - Matthew Koichi Grimes; Dragomir Anguelov; Yann LeCun (IROS, 2010)

Google Street View: Capturing the World at Street Level. - Dragomir Anguelov; Carole Dulong; Daniel Filip; Christian Früh; Stéphane Lafon; Richard Lyon; Abhijit S. Ogale; Luc Vincent; Josh Weaver (Computer, 2010)

Scalable Object Detection Using Deep Neural Networks. - Dumitru Erhan; Christian Szegedy; Alexander Toshev; Dragomir Anguelov (CVPR, 2014)

Capturing Long-Tail Distributions of Object Subcategories. - Xiangxin Zhu; Dragomir Anguelov; Deva Ramanan (CVPR, 2014)

Scalable, High-Quality Object Detection. - Christian Szegedy; Scott E. Reed; Dumitru Erhan; Dragomir Anguelov (CoRR, 2014)

Going deeper with convolutions. - Christian Szegedy; Wei Liu 015; Yangqing Jia; Pierre Sermanet; Scott E. Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke; Andrew Rabinovich (CVPR, 2015)

Training Deep Neural Networks on Noisy Labels with Bootstrapping. - Scott E. Reed; Honglak Lee; Dragomir Anguelov; Christian Szegedy; Dumitru Erhan; Andrew Rabinovich (ICLR (Workshop), 2015)

Self-informed neural network structure learning. - David Warde-Farley; Andrew Rabinovich; Dragomir Anguelov (ICLR (Workshop), 2015)

SSD: Single Shot MultiBox Detector. - Wei Liu 015; Dragomir Anguelov; Dumitru Erhan; Christian Szegedy; Scott E. Reed; Cheng-Yang Fu; Alexander C. Berg (ECCV (1), 2016)

Self-taught object localization with deep networks. - Loris Bazzani; Alessandro Bergamo; Dragomir Anguelov; Lorenzo Torresani (WACV, 2016)

3D Bounding Box Estimation Using Deep Learning and Geometry. - Arsalan Mousavian; Dragomir Anguelov; John Flynn; Jana Kosecka (CVPR, 2017)

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. - Danfei Xu; Dragomir Anguelov; Ashesh Jain (CVPR, 2018)

MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction. - Yuning Chai; Benjamin Sapp; Mayank Bansal; Dragomir Anguelov (CoRL, 2019)

End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds. - Yin Zhou; Pei Sun; Yu Zhang 033; Dragomir Anguelov; Jiyang Gao; Tom Ouyang; James Guo; Jiquan Ngiam; Vijay Vasudevan (CoRL, 2019)

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection. - Alex Bewley; Pei Sun; Thomas Mensink; Dragomir Anguelov; Cristian Sminchisescu (CoRL, 2020)

TNT: Target-driven Trajectory Prediction. - Hang Zhao; Jiyang Gao; Tian Lan; Chen Sun 002; Benjamin Sapp; Balakrishnan Varadarajan; Yue Shen; Yi Shen; Yuning Chai; Cordelia Schmid; Congcong Li; Dragomir Anguelov (CoRL, 2020)

VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation. - Jiyang Gao; Chen Sun 002; Hang Zhao; Yi Shen; Dragomir Anguelov; Congcong Li; Cordelia Schmid (CVPR, 2020)

Scalability in Perception for Autonomous Driving: Waymo Open Dataset. - Pei Sun; Henrik Kretzschmar; Xerxes Dotiwalla; Aurelien Chouard; Vijaysai Patnaik; Paul Tsui; James Guo; Yin Zhou; Yuning Chai; Benjamin Caine; Vijay Vasudevan; Wei Han 002; et al. (CVPR, 2020)

SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. - Zhenpei Yang; Yuning Chai; Dragomir Anguelov; Yin Zhou; Pei Sun; Dumitru Erhan; Sean Rafferty; Henrik Kretzschmar (CVPR, 2020)

STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction. - Zhishuai Zhang; Jiyang Gao; Junhua Mao; Yukai Liu; Dragomir Anguelov; Congcong Li (CVPR, 2020)

Improving 3D Object Detection Through Progressive Population Based Augmentation. - Shuyang Cheng; Zhaoqi Leng; Ekin Dogus Cubuk; Barret Zoph; Chunyan Bai; Jiquan Ngiam; Yang Song; Benjamin Caine; Vijay Vasudevan; Congcong Li; Quoc V. Le; Jonathon Shlens; et al. (ECCV (21), 2020)

Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout. - Zhao Chen; Jiquan Ngiam; Yanping Huang; Thang Luong; Henrik Kretzschmar; Yuning Chai; Dragomir Anguelov (NeurIPS, 2020)

SoDA: Multi-Object Tracking with Soft Data Association. - Wei-Chih Hung; Henrik Kretzschmar; Tsung-Yi Lin; Yuning Chai; Ruichi Yu; Ming-Hsuan Yang 001; Dragomir Anguelov (CoRR, 2020)

To the Point: Efficient 3D Object Detection in the Range Image With Graph Convolution Kernels. - Yuning Chai; Pei Sun; Jiquan Ngiam; Weiyue Wang 002; Benjamin Caine; Vijay Vasudevan; Xiao Zhang; Dragomir Anguelov (CVPR, 2021)

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. - Lu Mi; Hang Zhao; Charlie Nash; Xiaohan Jin; Jiyang Gao; Chen Sun 002; Cordelia Schmid; Nir Shavit; Yuning Chai; Dragomir Anguelov (CVPR, 2021)

Offboard 3D Object Detection From Point Cloud Sequences. - Charles R. Qi; Yin Zhou; Mahyar Najibi; Pei Sun; Khoa Vo 001; Boyang Deng; Dragomir Anguelov (CVPR, 2021)

RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection. - Pei Sun; Weiyue Wang 002; Yuning Chai; Gamaleldin Elsayed; Alex Bewley; Xiao Zhang; Cristian Sminchisescu; Dragomir Anguelov (CVPR, 2021)

Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. - Scott Ettinger; Shuyang Cheng; Benjamin Caine; Chenxi Liu 001; Hang Zhao; Sabeek Pradhan; Yuning Chai; Ben Sapp; Charles R. Qi; Yin Zhou; Zoey Yang; Aurelien Chouard; et al. (ICCV, 2021)

SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation. - Qiangeng Xu; Yin Zhou; Weiyue Wang 002; Charles R. Qi; Dragomir Anguelov (ICCV, 2021)

Identifying Driver Interactions via Conditional Behavior Prediction. - Ekaterina I. Tolstaya; Reza Mahjourian; Carlton Downey; Balakrishnan Varadarajan; Benjamin Sapp; Dragomir Anguelov (ICRA, 2021)

Revisiting 3D Object Detection From an Egocentric Perspective. - Boyang Deng; Charles R. Qi; Mahyar Najibi; Thomas A. Funkhouser; Yin Zhou; Dragomir Anguelov (NeurIPS, 2021)

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving. - Wenjie Luo; Cheol Park; Andre Cornman; Benjamin Sapp; Dragomir Anguelov (CoRL, 2022)

HUM3DIL: Semi-supervised Multi-modal 3D HumanPose Estimation for Autonomous Driving. - Andrei Zanfir; Mihai Zanfir; Alexander N. Gorban; Jingwei Ji; Yin Zhou; Dragomir Anguelov; Cristian Sminchisescu (CoRL, 2022)

Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving. - Jingxiao Zheng; Xinwei Shi; Alexander N. Gorban; Junhua Mao; Yang Song; Charles R. Qi; Ting Liu; Visesh Chari; Andre Cornman; Yin Zhou; Congcong Li; Dragomir Anguelov (CVPR Workshops, 2022)

RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding. - Xuanyu Zhou; Charles R. Qi; Yin Zhou; Dragomir Anguelov (CVPR, 2022)

CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection. - Jyh-Jing Hwang; Henrik Kretzschmar; Joshua Manela; Sean Rafferty; Nicholas Armstrong-Crews; Tiffany Chen; Dragomir Anguelov (ECCV (38), 2022)

Improving the Intra-class Long-Tail in 3D Detection via Rare Example Mining. - Chiyu Max Jiang; Mahyar Najibi; Charles R. Qi; Yin Zhou; Dragomir Anguelov (ECCV (10), 2022)

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. - Zhaoqi Leng; Shuyang Cheng; Benjamin Caine; Weiyue Wang 002; Xiao Zhang; Jonathon Shlens; Mingxing Tan; Dragomir Anguelov (ECCV (31), 2022)

LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. - Chenxi Liu 001; Zhaoqi Leng; Pei Sun; Shuyang Cheng; Charles R. Qi; Yin Zhou; Mingxing Tan; Dragomir Anguelov (ECCV (21), 2022)

LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds. - Minghua Liu; Yin Zhou; Charles R. Qi; Boqing Gong; Hao Su 001; Dragomir Anguelov (ECCV (39), 2022)

Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving. - Mahyar Najibi; Jingwei Ji; Yin Zhou; Charles R. Qi; Xinchen Yan; Scott Ettinger; Dragomir Anguelov (ECCV (38), 2022)

SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. - Pei Sun; Mingxing Tan; Weiyue Wang 002; Chenxi Liu 001; Fei Xia 005; Zhaoqi Leng; Dragomir Anguelov (ECCV (10), 2022)

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. - Zhaoqi Leng; Mingxing Tan; Chenxi Liu 001; Ekin Dogus Cubuk; Jay Shi; Shuyang Cheng; Dragomir Anguelov (ICLR, 2022)

Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. - Maximilian Igl; Daewoo Kim; Alex Kuefler; Paul Mougin; Punit Shah; Kyriacos Shiarlis; Dragomir Anguelov; Mark Palatucci; Brandyn White; Shimon Whiteson (ICRA, 2022)

Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking. - Longlong Jing; Ruichi Yu; Henrik Kretzschmar; Kang Li; Charles R. Qi; Hang Zhao; Alper Ayvaci; Xu Chen; Dillon Cower; Yingwei Li 002; Yurong You; Han Deng; et al. (ICRA, 2022)

StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving. - Jinkyu Kim 001; Reza Mahjourian; Scott Ettinger; Mayank Bansal; Brandyn White; Ben Sapp; Dragomir Anguelov (ICRA, 2022)

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction. - Balakrishnan Varadarajan; Ahmed Hefny; Avikalp Srivastava; Khaled S. Refaat; Nigamaa Nayakanti; Andre Cornman; Kan Chen; Bertrand Douillard; Chi-Pang Lam; Dragomir Anguelov; Benjamin Sapp (ICRA, 2022)

Multi-Class 3D Object Detection with Single-Class Supervision. - Mao Ye; Chenxi Liu 001; Maoqing Yao; Weiyue Wang 002; Zhaoqi Leng; Charles R. Qi; Dragomir Anguelov (ICRA, 2022)

Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. - Eli Bronstein; Mark Palatucci; Dominik Notz; Brandyn White; Alex Kuefler; Yiren Lu 001; Supratik Paul; Payam Nikdel; Paul Mougin; Hongge Chen; Justin Fu; Austin Abrams; et al. (IROS, 2022)

GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting. - Zhao Chen; Vincent Casser; Henrik Kretzschmar; Dragomir Anguelov (CoRR, 2022)

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. - Zhaoqi Leng; Mingxing Tan; Chenxi Liu 001; Ekin Dogus Cubuk; Xiaojie Shi; Shuyang Cheng; Dragomir Anguelov (CoRR, 2022)

Waymo Open Dataset: Panoramic Video Panoptic Segmentation. - Jieru Mei; Alex Zihao Zhu; Xinchen Yan; Hang Yan 002; Siyuan Qiao; Yukun Zhu; Liang-Chieh Chen; Henrik Kretzschmar; Dragomir Anguelov (CoRR, 2022)

LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations. - Zhaoqi Leng; Guowang Li; Chenxi Liu 001; Ekin Dogus Cubuk; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (CoRR, 2022)

HUM3DIL: Semi-supervised Multi-modal 3D Human Pose Estimation for Autonomous Driving. - Andrei Zanfir; Mihai Zanfir; Alexander N. Gorban; Jingwei Ji; Yin Zhou; Dragomir Anguelov; Cristian Sminchisescu (CoRR, 2022)

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving. - Wenjie Luo; Cheolho Park; Andre Cornman; Benjamin Sapp; Dragomir Anguelov (CoRR, 2022)

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. - Reza Mahjourian; Jinkyu Kim 001; Yuning Chai; Mingxing Tan; Ben Sapp; Dragomir Anguelov (IEEE Robotics Autom. Lett., 2022)

NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors. - Congyue Deng; Chiyu Max Jiang; Charles R. Qi; Xinchen Yan; Yin Zhou; Leonidas J. Guibas; Dragomir Anguelov (CVPR, 2023)

MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion. - Chiyu Max Jiang; Andre Cornman; Cheolho Park; Benjamin Sapp; Yin Zhou; Dragomir Anguelov (CVPR, 2023)

MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences. - Yingwei Li 002; Charles R. Qi; Yin Zhou; Chenxi Liu 001; Dragomir Anguelov (CVPR, 2023)

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild. - Bokui Shen; Xinchen Yan; Charles R. Qi; Mahyar Najibi; Boyang Deng; Leonidas J. Guibas; Yin Zhou; Dragomir Anguelov (CVPR, 2023)

3D Human Keypoints Estimation from Point Clouds in the Wild without Human Labels. - Zhenzhen Weng; Alexander S. Gorban; Jingwei Ji; Mahyar Najibi; Yin Zhou; Dragomir Anguelov (CVPR, 2023)

Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving. - Mahyar Najibi; Jingwei Ji; Yin Zhou; Charles R. Qi; Xinchen Yan; Scott Ettinger; Dragomir Anguelov (ICCV, 2023)

Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. - Zhaoqi Leng; Guowang Li; Chenxi Liu 001; Ekin Dogus Cubuk; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (ICRA, 2023)

LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. - Tong He; Pei Sun; Zhaoqi Leng; Chenxi Liu 001; Dragomir Anguelov; Mingxing Tan (IROS, 2023)

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. - Yiren Lu 001; Justin Fu; George Tucker; Xinlei Pan; Eli Bronstein; Rebecca Roelofs; Benjamin Sapp; Brandyn White; Aleksandra Faust; Shimon Whiteson; Dragomir Anguelov; Sergey Levine (IROS, 2023)

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. - Cole Gulino; Justin Fu; Wenjie Luo; George Tucker; Eli Bronstein; Yiren Lu 001; Jean Harb; Xinlei Pan; Yan Wang 051; Xiangyu Chen 007; John D. Co-Reyes; Rishabh Agarwal; et al. (NeurIPS, 2023)

The Waymo Open Sim Agents Challenge. - Nico Montali; John Lambert; Paul Mougin; Alex Kuefler; Nicholas Rhinehart; Michelle Li; Cole Gulino; Tristan Emrich; Zoey Yang; Shimon Whiteson; Brandyn White; Dragomir Anguelov (NeurIPS, 2023)

MoST: Multi-modality Scene Tokenization for Motion Prediction. - Norman Mu; Jingwei Ji; Zhenpei Yang; Nate Harada; Haotian Tang; Kan Chen; Charles R. Qi; Runzhou Ge; Kratarth Goel; Zoey Yang; Scott Ettinger; Rami Al-Rfou; et al. (CVPR, 2024)

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. - Kan Chen; Runzhou Ge; Hang Qiu 001; Rami Ai-Rfou; Charles R. Qi; Xuanyu Zhou; Zoey Yang; Scott Ettinger; Pei Sun; Zhaoqi Leng; Mustafa Baniodeh; Ivan Bogun; et al. (ICRA, 2024)

LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection. - Wei-Chih Hung; Vincent Casser; Henrik Kretzschmar; Jyh-Jing Hwang; Dragomir Anguelov (ICRA, 2024)

PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. - Zhaoqi Leng; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (ICRA, 2024)

SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout. - Chiyu Max Jiang; Yijing Bai; Andre Cornman; Christopher Davis; Xiukun Huang; Hong Jeon; Sakshum Kulshrestha; John Lambert; Shuangyu Li; Xuanyu Zhou; Carlos Fuertes; Chang Yuan; et al. (NeurIPS, 2024)

EMMA: End-to-End Multimodal Model for Autonomous Driving. - Jyh-Jing Hwang; Runsheng Xu; Hubert Lin; Wei-Chih Hung; Jingwei Ji; Kristy Choi; Di Huang; Tong He; Paul Covington; Benjamin Sapp; James Guo; Dragomir Anguelov; et al. (CoRR, 2024)

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation. - Yichen Xie 002; Runsheng Xu; Tong He; Jyh-Jing Hwang; Katie Luo; Jingwei Ji; Hubert Lin; Letian Chen; Yiren Lu 001; Zhaoqi Leng; Dragomir Anguelov; Mingxing Tan (CVPR, 2025)

SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model. - Shuhan Tan; John Lambert; Hong Jeon; Sakshum Kulshrestha; Yijing Bai; Jing Luo; Dragomir Anguelov; Mingxing Tan; Chiyu Max Jiang (CVPR, 2025)

SceneCrafter: Controllable Multi-View Driving Scene Editing. - Zehao Zhu; Yuliang Zou; Chiyu Max Jiang; Bo Sun; Vincent Casser; Xiukun Huang; Jiahao Wang; Zhenpei Yang; Ruiqi Gao; Leonidas J. Guibas; Mingxing Tan; Dragomir Anguelov (CVPR, 2025)

EMMA: End-to-End Multimodal Model for Autonomous Driving. - Jyh-Jing Hwang; Runsheng Xu; Hubert Lin; Wei-Chih Hung; Jingwei Ji; Kristy Choi; Di Huang; Tong He; Paul Covington; Benjamin Sapp; Yin Zhou; James Guo; et al. (Trans. Mach. Learn. Res., 2025)

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation. - Yichen Xie 002; Runsheng Xu; Tong He; Jyh-Jing Hwang; Katie Luo; Jingwei Ji; Hubert Lin; Letian Chen; Yiren Lu 001; Zhaoqi Leng; Dragomir Anguelov; Mingxing Tan (CoRR, 2025)

Scaling Laws of Motion Forecasting and Planning - A Technical Report. - Mustafa Baniodeh; Kratarth Goel; Scott Ettinger; Carlos Fuertes; Ari Seff; Tim Shen; Cole Gulino; Chenjie Yang; Ghassen Jerfel; Dokook Choe; Rui Wang; Vinutha Kallem; et al. (CoRR, 2025)