Search papers, labs, and topics across Lattice.
Xiamen University
6
0
7
OmniView-Space redefines spatial reasoning in MLLMs, achieving unprecedented accuracy by leveraging dynamic, egocentric evidence mapping.
QCA selects the most relevant frames from long videos, achieving superior performance with half the data of previous methods.
SAGE transforms failure recovery in autonomous research by generating multiple grounded explanations, leading to a dramatic increase in reliable scientific outputs.
CausalMem achieves over 20x visual token compression while maintaining high accuracy in streaming video understanding, redefining memory efficiency in MLLMs.
AdaQ enables MLLMs to achieve superior long video understanding with just 64 frames, outperforming state-of-the-art methods by a striking margin.
Autoregressive video generation gets a 6x speed boost without sacrificing quality, thanks to a motion-aware caching strategy that finally respects the fact that not all pixels are created equal.
