4 citations · 4 across the 9 of their papers we have counts for
9 papers
OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs
Haoyang Huang, Wenjie Huang, Tianqi Xu +14
Emerging Omni-modal Large Language Models (OmniLLMs) enable unified understanding of text, audio, and video, but their long audio-video token sequences introduce substantial memory…
HDRFace: Rethinking Face Restoration with High-Dimensional Representation
Zirui Wang, Xianhui Lin, Yi Dong +7
Face restoration under complex degradations still remains an ill-posed inverse problem due to severe information loss. Although diffusion models benefit from strong generative prio…
TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
Hongyaoxing Gu, Xinzhe Chen, Lijuan Hu +1
Mixture-of-Experts (MoE) models achieve remarkable performance by sparsely activating specialized experts, yet their massive parameters in experts pose significant challenges for d…
LoPRo: Enhancing Low-Rank Quantization via Permuted Block-Wise Rotation
Hongyaoxing Gu, Lijuan Hu, Liye Yu +2
Post-training quantization (PTQ) enables effective model compression while preserving relatively high accuracy. Current weight-only PTQ methods primarily focus on the challenging s…
FLRQ: Faster LLM Quantization with Flexible Low-Rank Matrix Sketching
Hongyaoxing Gul, Lijuan Hu, Shuzi Niu +1
Traditional post-training quantization (PTQ) is considered an effective approach to reduce model size and accelerate inference of large-scale language models (LLMs). However, exist…
A method of using RSVD in residual calculation of LowBit GEMM
Hongyaoxing Gu
The advancements of hardware technology in recent years has brought many possibilities for low-precision applications. However, the use of low precision can introduce significant c…
LRAMM -- Low precision approximates GEMM via RSVD
Hongyaoxing Gu
Matrix multiplication computation acceleration has been a research hotspot across various domains. Due to the characteristics of some applications, approximate matrix multiplicatio…
A method for accelerating low precision operations by sparse matrix multiplication
Hongyaoxing Gu
In recent years, the fervent demand for computational power across various domains has prompted hardware manufacturers to introduce specialized computing hardware aimed at enhancin…
A differentiable brain simulator bridging brain simulation and brain-inspired computing
Chaoming Wang, Tianqiu Zhang, Sichao He +3
Brain simulation builds dynamical models to mimic the structure and functions of the brain, while brain-inspired computing (BIC) develops intelligent systems by learning from the s…