Search papers, labs, and topics across Lattice.
Affiliation:
7
0
14
A frozen video tokenizer's latent can be factored into controllable and reward-relevant components, unlocking significant downstream planning gains.
This work describes an automatic criterion for full-state rejuvenation of the Gibbs sampler, derived from the Gelman-Rubin statistic, which plays a key role in speeding up learning convergence.
Targeted non-literal suppression in LLMs reveals a critical trade-off between compliance and output quality that could redefine copyright defense strategies.
Compact retrievers can achieve nearly half the performance of larger models while being up to 9.7脳 faster, challenging the assumption that bigger is always better in retrieval tasks.
Transforming noisy web text into a high-quality petroleum engineering dataset boosts retrieval performance by over 44% on benchmark tasks.
Layer span variation can unlock a new dimension of deterministic rollout diversity, boosting performance by over 10 percentage points on reasoning tasks.
Forget retraining: HyperKKL uses a hypernetwork to dynamically condition KKL observers on exogenous inputs, enabling accurate state estimation for non-autonomous nonlinear systems.
