2 citations · 5 across the 12 of their papers we have counts for
5 papers · 1 filter
CommunityKV: Efficient Long-Context Decoding via Graph Partitioning
Joe McKenna, Anastasios Alexandridis, Nathan Susanj +1
Scaling Transformers to long contexts is constrained by the quadratic cost of self-attention and the linear growth of key-value cache memory transfer. Sparse attention mitigates th…
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes
Yifan Yang, Zhen Zhang, Rupak Vignesh Swaminathan +3
Fine-tuning vision language models (VLMs) has achieved remarkable performance across various downstream tasks; yet, it requires access to model gradients through backpropagation (B…
Wanda++: Pruning Large Language Models via Regional Gradients
Yifan Yang, Kai Zhen, Bhavana Ganesh +11
Large Language Models (LLMs) pruning seeks to remove unimportant weights for inference speedup with minimal accuracy impact. However, existing methods often suffer from accuracy de…
MaZO: Masked Zeroth-Order Optimization for Multi-Task Fine-Tuning of Large Language Models
Zhen Zhang, Yifan Yang, Kai Zhen +4
Large language models have demonstrated exceptional capabilities across diverse tasks, but their fine-tuning demands significant memory, posing challenges for resource-constrained…
Accelerator-Aware Training for Transducer-Based Speech Recognition
Suhaila M. Shakiah, Rupak Vignesh Swaminathan, Hieu Duy Nguyen +6
Machine learning model weights and activations are represented in full-precision during training. This leads to performance degradation in runtime when deployed on neural network a…