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cs.LG2025
IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adaptation
Yuan Yin, Shashanka Venkataramanan, Tuan-Hung Vu +2
Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, reduce adaptation cost by injecting low-rank updates into pretrained weights. However, LoRA's down-projection is rando…
cs.LG2024
ReGentS: Real-World Safety-Critical Driving Scenario Generation Made Stable
Yuan Yin, Pegah Khayatan, Éloi Zablocki +2
Machine learning based autonomous driving systems often face challenges with safety-critical scenarios that are rare in real-world data, hindering their large-scale deployment. Whi…