Jiangxia Cao

Summary tokens are not just compressed context, but also dynamic KV cache indices, unlocking flexible memory compression and reduced compute in hybrid attention.

Non-monotonic performance in experimental trajectories reveals that later rounds can sometimes undermine earlier successes, challenging conventional assumptions in industrial ML research.

Behavior-derived rewards enable MLLMs to generate effective recommendations without user-specific data at inference, outperforming traditional methods.