4 citations · 5 across the 7 of their papers we have counts for
9 papers
Where Small Mistakes Matter: Quantifying State Criticality for Imitation Learning
Yusuf Umut Ciftci, Joonwon Kang, Ajay Suresha Sathya +1
Imitation learning typically treats every demonstration state as equally important, optimizing a behavior-cloning objective uniformly across the dataset. Yet not all states are cre…
FineART: Fine-Grained Annotated Robotic Trajectory Dataset and Vision-Language-Action Model for Bimanual Manipulation
Jade Choghari, Pepijn Kooijmans, Mansi Agarwal +8
Robots operating in real-world environments must often execute complex, multi-step bimanual tasks over long horizons rather than single, isolated actions. Current manipulation data…
Adaptive Time Step Flow Matching for Autonomous Driving Motion Planning
Ananya Trivedi, Anjian Li, Mohamed Elnoor +7
Autonomous driving requires reasoning about interactions with surrounding traffic. A prevailing approach is large-scale imitation learning on expert driving datasets, aimed at gene…
Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection
Le Qiu, Yusuf Umut Ciftci, Somil Bansal
Imitation Learning has provided a promising approach to learning complex robot behaviors from expert demonstrations. However, learned policies can make errors that lead to safety v…
Unsupervised Discovery of Failure Taxonomies from Deployment Logs
Aryaman Gupta, Yusuf Umut Ciftci, Somil Bansal
As robotic systems become increasingly integrated into real-world environments, ranging from autonomous vehicles to household assistants, they inevitably encounter diverse and unst…
DualGuard MPPI: Safe and Performant Optimal Control by Combining Sampling-Based MPC and Hamilton-Jacobi Reachability
Javier Borquez, Luke Raus, Yusuf Umut Ciftci +1
Designing controllers that are both safe and performant is inherently challenging. This co-optimization can be formulated as a constrained optimal control problem, where the cost f…
Stable-BC: Controlling Covariate Shift with Stable Behavior Cloning
Shaunak A. Mehta, Yusuf Umut Ciftci, Balamurugan Ramachandran +2
Behavior cloning is a common imitation learning paradigm. Under behavior cloning the robot collects expert demonstrations, and then trains a policy to match the actions taken by th…
Do LLMs Recognize me, When I is not me: Assessment of LLMs Understanding of Turkish Indexical Pronouns in Indexical Shift Contexts
Metehan Oğuz, Yusuf Umut Ciftci, Yavuz Faruk Bakman
Large language models (LLMs) have shown impressive capabilities in tasks such as machine translation, text summarization, question answering, and solving complex mathematical probl…
SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems
Yusuf Umut Ciftci, Darren Chiu, Zeyuan Feng +2
Behavior cloning (BC) is a widely-used approach in imitation learning, where a robot learns a control policy by observing an expert supervisor. However, the learned policy can make…