Search papers, labs, and topics across Lattice.
4
0
5
4
This work proposes ASPIRE, a non-synchronized batched self-speculative decoding framework built on three components, which achieves speedup in decoding throughput over autoregressive baselines and improves average speedup by approximately $27\% over the strongest prior self-speculative baselines.
STAIR achieves a remarkable 16.57% improvement in F1 scores by separating semantic interpretation from temporal inference, making temporal reasoning both interpretable and verifiable.
BCSD enables LLM agents to leverage external skills more effectively, achieving superior performance by integrating dual-context evaluations.
Substantial IP leakage risks in autonomous multi-agent systems are revealed through a novel framework that extracts harness capabilities dynamically during inference.
