From the 1 of 6 linked papers with an AI index.
6 papers
Steering Robustness into World Action Models via Mechanistic Interpretability and Optimal Control
Jihoon Hong, Julian Skifstad, Qiyue Dai +2
The paper investigates how to improve the robustness of World Action Models (WAMs) by analyzing their internal activations with mechanistic interpretability and applying a model‑ba…
Activation Steering of Video Generation Models via Reduced-Order Linear Optimal Control
Jihoon Hong, Alice Chan, Qiyue Dai +2
Text-to-video (T2V) models trained on large-scale web data can generate undesired content, motivating interventions that reduce harmful outputs without sacrificing visual quality.…
ATLAS: A Large-Scale Evaluation Benchmark for Adversarial LiDAR Perception
Mellon M. Zhang, Siddhant Panse, Zimo Fan +3
Autonomous driving perception is typically evaluated on clean benchmark data, yet real-world deployment requires robustness to rare, structured, and potentially adversarial sensor…
Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
Julian Skifstad, Xinyue Annie Yang, Glen Chou
Inference-time LLM alignment methods, particularly activation steering, offer an alternative to fine-tuning by directly modifying activations during generation. Existing methods, h…
Towards Streaming LiDAR Object Detection with Point Clouds as Egocentric Sequences
Mellon M. Zhang, Glen Chou, Saibal Mukhopadhyay
Accurate and low-latency 3D object detection is essential for autonomous driving, where safety hinges on both rapid response and reliable perception. While rotating LiDAR sensors a…
MAPS: Preserving Vision-Language Representations via Module-Wise Proximity Scheduling for Better Vision-Language-Action Generalization
Chengyue Huang, Mellon M. Zhang, Robert Azarcon +2
Vision-Language-Action (VLA) models inherit strong priors from pretrained Vision-Language Models (VLMs), but naive fine-tuning often disrupts these representations and harms genera…