2 papers
cs.LG2026
ABNAT: Attention-Based Noise-Aware Training for Robust Transformers on Analog Compute-in-Memory Systems
Wenshuai Yao, Wenyong Zhou, Hanyong Shao +5
Transformer-based models have become the backbone of a wide range of tasks, but their intensive computation and data movement incur substantial energy overhead. Analog compute-in-m…
cs.CL2026
Share the Symbol, Not the Vector: Training-Free Fact Communication Across Language Models
Xin Li, Mengbing Liu, Hao Jiang +5
Multi-agent systems allow language models to solve tasks collaboratively by sharing complementary information. These systems typically communicate through text, while recent approa…