Publications

Robot Learning

• Physical Intelligence et al. : a Steerable Generalist Robotic Foundation Model with Emergent Capabilities. arXiv preprint arXiv:2604.15483, 2026. [website] [pdf]
• Marcel Torne et al. MEM: Multi-Scale Embodied Memory for Vision Language Action Models. arXiv preprint arXiv:2603.03596, 2026. [website] [pdf]
• Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton. Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. Thirteenth International Conference on Learning Representations (ICLR), 2025. [website] [pdf]

3D Vision / Scene Flow

• Siyi Li, Qingwen Zhang, Ishan Khatri, Kyle Vedder, Eric Eaton, Deva Ramanan, Neehar Peri. UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles. arXiv preprint arXiv:2511.18254, 2025. [website] [pdf]
• Kyle Vedder. Toward Scalable, Flexible Scene Flow for Point Clouds. Ph.D. Dissertation, 2025. [pdf]
• Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl. Neural Eulerian Scene Flow Fields. Thirteenth International Conference on Learning Representations (ICLR), 2025. [website] [pdf]
• Ishan Khatri*, Kyle Vedder*, Neehar Peri, Deva Ramanan, James Hays. I Can’t Believe It’s Not Scene Flow!. European Conference on Computer Vision (ECCV), 2024. [website] [pdf]
• Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays. ZeroFlow: Scalable Scene Flow via Distillation. Twelfth International Conference on Learning Representations (ICLR), 2024. [website] [pdf]
• Kyle Vedder, Ishan Khatri, Neehar Peri, Nate Chodosh, Yang Liu, James Hays. Argoverse 2 2024 Scene Flow Challenge at the CVPR 2024 Workshop on Autonomous Driving. 2024. [website]
• Kyle Vedder, Eric Eaton. Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems. Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2022. [website] [pdf]
• Kyle Vedder, Eric Eaton. Sparse PointPillars: Exploiting Sparsity on Birds-Eye-View Object Detection. Sparsity in Neural Networks Workshop (SNN), 2021. [pdf] [poster]
• Kyle Vedder. Current Approaches and Future Directions for Point Cloud Object Detection in Intelligent Agents. 2021. [pdf] [slides] [video]

Multi-Agent Robotics and Path Planning

• Kyle Vedder, Joydeep Biswas. X*: Anytime Multi-Agent Path Finding For Sparse Domains Using Window-Based Iterative Repairs. Artificial Intelligence (AIJ), 2021. [website] [pdf]
• Kyle Vedder, Joydeep Biswas. X*: Anytime Multiagent Path Planning With Bounded Search. Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2019. [website] [pdf]
• Kyle Vedder, Edward Schneeweiss, Sadegh Rabiee, Samer Nashed, Spencer Lane, Jarrett Holtz, Joydeep Biswas, David Balaban. UMass MinuteBots 2018 Team Description Paper. 2018. [pdf]
• Spencer Lane, Kyle Vedder, Joydeep Biswas. Augmenting Planning Graphs in 2-Dimensional Dynamic Environments With Obstacle Scaffolds. Proceedings of the 5th Workshop on Planning and Robotics (ICAPS PlanRob), 2017. [pdf]
• Kyle Vedder, Edward Schneeweiss, Sadegh Rabiee, Samer Nashed, Spencer Lane, Jarrett Holtz, Joydeep Biswas, David Balaban. UMass MinuteBots 2017 Team Description Paper. 2017. [pdf]

Other

• Andrea Soltoggio et al. A collective AI via lifelong learning and sharing at the edge. Nature Machine Intelligence, 2024. [pdf]
• Megan M. Baker et al. A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks, 2023. [pdf]
• Kyle Vedder. An Overview of SHAP-based Feature Importance Measures and Their Applications To Classification. 2020. [pdf] [slides] [video]