Search papers, labs, and topics across Lattice.
L1), introduces explicit counterfactual by providing both the altered objective laws and their outcomes (L
3
0
6
T2I models falter dramatically in counterfactual scenarios, revealing their dependence on familiar visual patterns rather than true causal reasoning.
MiniMax-M2 proves that massive parameter counts don't always translate to better agentic performance; strategic activation of a smaller subset can unlock frontier-level intelligence.
Forget agents and world models – the future of computing could be learned directly from I/O traces, turning the model itself into the computer.
