Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds
Introduction A game world built by a video generation model alone stores off-screen state nowhere. Every time a corridor you have already passed through is redrawn, it…
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Rethinking Sequence Compression with Test-time Regression
Introduction In models that handle long contexts, the compression operation that reduces multiple tokens to a single vector becomes a performance bottleneck. This paper…
Large Flow Language Models
The sequential bottleneck of sampling one token at a time Large language models can compute an entire sentence in parallel during training, but when generating text they…
Cache Engineering for Agents
The Cost and Accuracy Dilemma of Long Agent Trajectories LLM agents accumulate long trajectories by repeating reasoning and tool calls for hundreds of rounds. To make…
Speculative Sampling in Interactive Video Generation
Speculative sampling reuses future video predictions to reduce response latency. How it works, recomputation costs, and the limits of the serving experiments.
MemT-1.0: Towards Memory-Native Evolution
MemT-1.0 stores conversation history in a fixed-size matrix state. We examine memory updates, information loss, and how the approach compares with full-context and…