Search papers, labs, and topics across Lattice.
4
7
6
7
LLM agent progress increasingly hinges on better external cognitive infrastructure, not just stronger models.
LMM-based GUI agents stick out like a sore thumb in human-centric mobile environments, but simple techniques can make them blend in without sacrificing utility.
GUI agents learn faster and generalize better with a new reward shaping technique that dynamically adapts to successful exploration trajectories, outperforming fixed reward schemes.
Current LLM evaluation benchmarks often conflate chatbots and true AI agents, leading to misaligned research efforts, but this survey provides a framework for targeted evaluation based on environmental complexity and agent capabilities.
