3 papers
cs.CV2026
CLASP: Class-Adaptive Layer Fusion and Dual-Stage Pruning for Multimodal Large Language Models
Yunkai Dang, Yizhu Jiang, Yifan Jiang +4
Multimodal Large Language Models (MLLMs) suffer from substantial computational overhead due to the high redundancy in visual token sequences. Existing approaches typically address…
cs.ET2025
StochEP: Stochastic Equilibrium Propagation for Spiking Convergent Recurrent Neural Networks
Jiaqi Lin, Yi Jiang, Abhronil Sengupta
Spiking Neural Networks (SNNs) promise energy-efficient, sparse, biologically inspired computation. Training them with Backpropagation Through Time (BPTT) and surrogate gradients a…
cs.NE2025
Spatio-Temporal Pruning for Compressed Spiking Large Language Models
Yi Jiang, Malyaban Bal, Brian Matejek +3
Large Language Models (LLMs) present significant challenges for deployment in energy-constrained environments due to their large model sizes and high inference latency. Spiking Neu…