Search papers, labs, and topics across Lattice.
Affiliation:
5
0
6
0
Audio and acceleration modalities can predict physical interactions with surprising accuracy, but the executor's architecture is the true bottleneck in achieving effective multimodal execution.
DentAgent outperforms senior specialists by 17.3 percentage points in multi-label diagnosis, revolutionizing multimodal dental reasoning with traceable evidence integration.
Learning from user interactions, AgentAntibody evolves to effectively defend LLM agents against prompt injection, outperforming static defenses.
Prediction objectives shape the physical knowledge embedded in latent representations, revealing that some parameters are only captured under specific forecasting conditions.
Adapters may store less than half the information expected, with their capacity heavily influenced by parameter placement rather than quantity.
