14 papers
COEC: Calibrated Orthogonal-Equivalence Compensation for Structured Pruning of Large Language Models
Peiqi Yu, Nam Ling, Wei Wang +1
Structured pruning reduces the size and inference cost of large language models (LLMs) by removing weight columns, but the resulting output error can degrade accuracy. Existing tra…
CORAM: Coherent Orthogonal Rotation for Model Merging
Xinyi Sui, Ziran Liu, Nam Ling +2
Merging finetuned models combines specialized capabilities without joint training or access to the original data. Most methods operate by linear arithmetic in Euclidean weight spac…
Adaptive Fused Prior Transfer for Controllable Generative Image Compression
Yifei Pei, Ying Liu, Nam Ling
Learned image compression has achieved competitive rate-distortion performance, but very-low-bitrate reconstruction remains difficult because the transmitted representation often c…
Geometric and Spectral Alignment for Deep Neural Network II
Ziran Liu, Wei Wang, Jinhao Wang +5
This paper develops the angular and static-channel component of Geometric and Spectral Alignment for residual Jacobian chains. Starting from Cartan-coordinate rigidity and fitted e…
Geometric and Spectral Alignment for Deep Neural Network I
Ziran Liu, Wei Wang, Jinhao Wang +5
Deep residual architectures are modeled as products of near-identity Jacobians. This paper proves deterministic quotient-geometric estimates for singular spectra of Frobenius-norma…
What Did They Mean? How LLMs Resolve Ambiguous Social Situations across Perspectives and Roles
Qiming Yuan, Linyi Han, Nam Ling +1
People increasingly turn to large language models (LLMs) to interpret ambiguous social situations: a delayed text reply, an unusually cold supervisor, a teacher's mixed signals, or…