3 papers
cs.LG2026
GLASS: Global-Local Aggregation for Inference-time Sparsification of LLMs
Amirmohsen Sattarifard, Sepehr Lavasani, Kunlin Zhang +5
Inference-time sparsification is a promising path to deploy large language models (LLMs) on resource-constrained devices, yet existing training-free methods typically estimate feed…
cs.CV2025
Grounding Degradations in Natural Language for All-In-One Video Restoration
Muhammad Kamran Janjua, Amirhosein Ghasemabadi, Kunlin Zhang +3
In this work, we propose an all-in-one video restoration framework that grounds degradation-aware semantic context of video frames in natural language via foundation models, offeri…
cs.LG2025
Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone
Negar Hassanpour, Muhammad Kamran Janjua, Kunlin Zhang +4
Balancing competing objectives remains a fundamental challenge in multi-task learning (MTL), primarily due to conflicting gradients across individual tasks. A common solution relie…