Search papers, labs, and topics across Lattice.
5
0
9
SLMs can match the reasoning performance of much larger models by simply re-ranking their own top-K token predictions, eliminating the need for expensive LLM calls at inference time.
LLM agents can get 18% better at tasks by co-evolving their skills and tools, instead of learning them separately.
Ditch the router: this MoE architecture lets experts decide when to activate, leading to better scalability and robustness.
LVLMs can reason about video streams *much* faster and better by thinking concurrently with the incoming data, not in batches.
LLMs actually *do* improve time series forecasting, especially for cross-domain generalization, overturning prior doubts with a massive 8-billion observation study.
