Search papers, labs, and topics across Lattice.
5
0
12
0
Agents can now explore environments more efficiently by thinking like humans, prioritizing key landmarks and semantic information during online memory construction.
Frozen LLMs can dynamically improve their reasoning abilities at test time, without any training, by distilling knowledge from their own successes and failures.
LLMs still struggle to accurately infer user interests from interaction histories, especially when dealing with diverse engagement signals – a critical gap for effective personalization.
LLMs can automatically design better heuristics for combinatorial optimization, leading to state-of-the-art results on large-scale CVRP instances.
Forget task-specific architectures: a single Vision-Language-Action foundation model, ABot-N0, now dominates embodied navigation across five distinct tasks.
