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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.CL2025
Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence
Amirhosein Ghasemabadi, Keith G. Mills, Baochun Li +1
Test-Time Scaling (TTS) methods for enhancing Large Language Model (LLM) reasoning often incur substantial computational costs, primarily due to extensive reliance on external Proc…