1 citations · 1 across the 13 of their papers we have counts for
13 papers
DARE: Diffusion Language Model Activation Reuse for Efficient Inference
Natalia Frumkin, Bokun Wang, Hung-Yueh Chiang +3
Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to auto-regressive (AR) models, offering greater expressive capacity and potential for parallel gene…
SkipCat: Rank-Maximized Low-Rank Compression of Large Language Models via Shared Projection and Block Skipping
Yu-Chen Lu, Sheng-Feng Yu, Hui-Hsien Weng +5
Large language models (LLM) have achieved remarkable performance across a wide range of tasks. However, their substantial parameter sizes pose significant challenges for deployment…
ELANA: A Simple Energy and Latency Analyzer for LLMs
Hung-Yueh Chiang, Bokun Wang, Diana Marculescu
The latency and power consumption of large language models (LLMs) are major constraints when serving them across a wide spectrum of hardware platforms, from mobile edge devices to…
UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs
Hung-Yueh Chiang, Chi-Chih Chang, Yu-Chen Lu +4
Deploying large language models (LLMs) on mobile platforms faces significant challenges due to the limited memory and shared computational resources of the device. Resource availab…
QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models
Tien-Yu Chi, Hung-Yueh Chiang, Diana Marculescu +1
State space models (SSMs) reduce the quadratic complexity of transformers by leveraging linear recurrence. Recently, VMamba has emerged as a strong SSM-based vision backbone, yet r…
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin +3
State Space Models (SSMs) are emerging as a compelling alternative to Transformers because of their consistent memory usage and high performance. Despite this, scaling up SSMs on c…
xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
Chi-Chih Chang, Wei-Cheng Lin, Chien-Yu Lin +8
Long-context Large Language Models (LLMs) enable powerful applications but incur high memory costs due to the key-value states (KV-Cache). Recent studies attempt to share KV-Cache…
Similarity Trajectories: Linking Sampling Process to Artifacts in Diffusion-Generated Images
Dennis Menn, Feng Liang, Hung-Yueh Chiang +1
Artifact detection algorithms are crucial to correcting the output generated by diffusion models. However, because of the variety of artifact forms, existing methods require substa…
V"Mean"ba: Visual State Space Models only need 1 hidden dimension
Tien-Yu Chi, Hung-Yueh Chiang, Chi-Chih Chang +2
Vision transformers dominate image processing tasks due to their superior performance. However, the quadratic complexity of self-attention limits the scalability of these systems a…
Quamba: A Post-Training Quantization Recipe for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin +2
State Space Models (SSMs) have emerged as an appealing alternative to Transformers for large language models, achieving state-of-the-art accuracy with constant memory complexity wh…
SCAN-Edge: Finding MobileNet-speed Hybrid Networks for Diverse Edge Devices via Hardware-Aware Evolutionary Search
Hung-Yueh Chiang, Diana Marculescu
Designing low-latency and high-efficiency hybrid networks for a variety of low-cost commodity edge devices is both costly and tedious, leading to the adoption of hardware-aware neu…
Efficient Low-rank Backpropagation for Vision Transformer Adaptation
Yuedong Yang, Hung-Yueh Chiang, Guihong Li +2
The increasing scale of vision transformers (ViT) has made the efficient fine-tuning of these large models for specific needs a significant challenge in various applications. This…
FOX-NAS: Fast, On-device and Explainable Neural Architecture Search
Chia-Hsiang Liu, Yu-Shin Han, Yuan-Yao Sung +3
Neural architecture search can discover neural networks with good performance, and One-Shot approaches are prevalent. One-Shot approaches typically require a supernet with weight s…