From the 1 of 6 linked papers with an AI index.
6 papers
Lie-Algebraic Subspace Quantization for Zero-Shot Quantum Learning and Barren-Plateau Mitigation
Yuhan Yao, Yoshihiko Hasegawa
The paper introduces a Lie‑algebraic subspace quantization method that maps classical neural‑network weights onto low‑dimensional quantum evolutions, enabling zero‑shot quantum lea…
Foundation Models for Trajectory Planning in Autonomous Driving: A Review of Progress and Open Challenges
Kemal Oksuz, Alexandru Buburuzan, Anthony Knittel +2
The emergence of multi-modal foundation models has markedly transformed the technology for autonomous driving, shifting away from conventional and mostly hand-crafted design choice…
RooflineBench: A Benchmarking Framework for On-Device LLMs via Roofline Analysis
Zhen Bi, Xueshu Chen, Luoyang Sun +4
The transition toward localized intelligence through Small Language Models (SLMs) has intensified the need for rigorous performance characterization on resource-constrained edge ha…
Gradient Analysis of Barren Plateau in Parameterized Quantum Circuits with multi-qubit gates
Yuhan Yao, Yoshihiko Hasegawa
The emergence of the Barren Plateau phenomenon poses a significant challenge to quantum machine learning. While most Barren Plateau analyses focus on single-qubit rotation gates, t…
Delta Sampling: Data-Free Knowledge Transfer Across Diffusion Models
Zhidong Gao, Zimeng Pan, Yuhang Yao +2
Diffusion models like Stable Diffusion (SD) drive a vibrant open-source ecosystem including fully fine-tuned checkpoints and parameter-efficient adapters such as LoRA, LyCORIS, and…
Direct Gradient Computation for Barren Plateaus in Parameterized Quantum Circuits
Yuhan Yao, Yoshihiko Hasegawa
The barren plateau phenomenon, where the gradients of parametrized quantum circuits become vanishingly small, poses a significant challenge in quantum machine learning. While previ…