4 papers
Cache the Encoder Within:Compact, Reusable Memory across LLM Queries
Hanzuo Liu, Chunyu Liu, Chaofan Lin +2
Repeated queries over shared documents incur redundant encoding, while caching model states introduces persistent storage costs. Building on CoMem's intermediate-state interface, E…
Frozen in a Frame: The Velocity Blind Spot in JEPA World Models
Tinghe Zhang, Chunyu Liu, Yu Leon Liu +6
Joint-embedding predictive architectures (JEPAs) for world modeling train an encoder so a predictor maps a current embedding and action to the next frame's embedding, always from a…
CoMem: Reusing Transformer Depth across Queries with Persistent Intermediate Residuals
Hanzuo Liu, Xuan Qi, Chunyu Liu +6
Repeated queries over shared documents repeatedly execute the same lower transformer layers. We introduce CoMem, which makes split depth j an explicit reusable-context axis: write…
VoidPadding: Let [VOID] Handle Padding in Masked Diffusion Language Models so that [EOS] Can Focus on Semantic Termination
Chunyu Liu, Zhengyang Fan, Kaisen Yang +1
MDLMs generate text by denoising a preallocated masked response canvas, making response-length modeling central to instruction tuning. Existing MDLMs often inherit the autoregressi…