From the 1 of 13 linked papers with an AI index.
13 papers
Riemannian Deep Learning: Modules, Networks, and Geometries
Ziheng Chen, Chen Ziheng
Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific manifolds, rely on Euclidean approximatio…
LieBN: Batch Normalization over Lie Groups
Ziheng Chen, Yue Song, Rui Wang +2
The paper introduces LieBN, a batch‑normalization framework that works on data lying on Lie groups, providing theoretical control of Riemannian mean and variance across several com…
Discontinuous Prior-Mode Sections and the Geometry of Ambiguity in Intrinsic Image Decomposition
Ziheng Chen, Liangchen Liu, Qishi Zhan +2
The viral 2015 photograph known as "The Dress" divides observers into two camps because it is ambiguous: the same image colors can be explained either as a blue-black surface under…
Disentangling Language Roles in Multilingual LLM Task Execution
Qishi Zhan, Minxuan Hu, Seoyeon Jang +7
Multilingual LLMs are increasingly used when instruction, source content, and required response languages do not coincide. Existing benchmarks have expanded multilingual instructio…
Relative Repairability: A Calibration-Based Diagnostic for High-Sparsity Post-Pruning Allocation
Qishi Zhan, Liang He, Minxuan Hu +1
At very high sparsity, neural network pruning does more than decide which weights remain. It also determines where pruning induced damage is placed across the network, and whether…
Adaptive Signal Resuscitation: Channel-wise Post-Pruning Repair for Sparse Vision Networks
Qishi Zhan, Ziheng Chen, Minxuan Hu
One-shot magnitude pruning can cause severe accuracy collapse in the high-sparsity regime, even when the pruning mask preserves the largest weights. We argue that this failure refl…