10 papers
Supportive Token Revealing for Fast Diffusion Language Model Decoding
Giries Abu Ayoub, Mario Barbara, LluÃs Pastor-Pérez +4
Discrete diffusion language models can generate text efficiently by updating multiple masked positions in parallel, but this parallelism introduces a quality-latency trade-off. Agg…
Efficient Test-Time Finetuning of LLMs via Convex Reconstruction and Gradient Caching
Alaa Khamis, Alaa Maalouf
Test-time finetuning (TTFT) is a rapidly evolving paradigm that adapts a language model to each prompt by retrieving related sequences, updating the model on them, and then evaluat…
Autonomous Sea Turtle Robot for Marine Fieldwork
Zach J. Patterson, Emily Sologuren, Levi Cai +4
Autonomous robots can transform how we observe marine ecosystems, but close-range operation in reefs and other cluttered habitats remains difficult. Vehicles must maneuver safely n…
Prompts to Summaries: Zero-Shot Language-Guided Video Summarization with Large Language and Video Models
Mario Barbara, Alaa Maalouf
The explosive growth of video data intensified the need for flexible user-controllable summarization tools that operate without training data. Existing methods either rely on domai…
Robustness Is a Function, Not a Number: A Factorized Comprehensive Study of OOD Robustness in Vision-Based Driving
Amir Mallak, Alaa Maalouf
Out of distribution (OOD) robustness in autonomous driving is often reduced to a single number, hiding what breaks a policy. We decompose environments along five axes: scene (rural…
See Less, Drive Better: Generalizable End-to-End Autonomous Driving via Foundation Models Stochastic Patch Selection
Amir Mallak, Erfan Aasi, Shiva Sreeram +3
Recent advances in end-to-end autonomous driving show that policies trained on patch-aligned features extracted from foundation models generalize better to Out-of-Distribution (OOD…