attention dynamics 1efficiency 1multimodal large language models 1token pruning 1training-free methods 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.CV2026
Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models
Jie Ma, Zhike Qiu, Jie Gao +4
The paper introduces Trend-aware Pruning, a training‑free method that models the temporal dynamics of attention to selectively keep visual tokens that become important in deeper la…
cs.AI2026
Beyond Tracking or Shortcut: Composition-Bounded Predictive States in Poker Autoregressive Models
Quanhao Li, Qianyu Chen
Hidden-state probes often recover latent labels in imperfect-information sequence models, but this alone does not establish that a model maintains a posterior belief distribution o…