Search papers, labs, and topics across Lattice.
5
0
7
0
Reflection in search agents can be transformed into a powerful memory-control policy, leading to superior performance in complex reasoning tasks.
"Parallel Shapley effectively 'fishes out the free riders' in reasoning paths, leading to more stable and interpretable training outcomes for LLMs."
KbSD transforms the way agentic search models navigate knowledge boundaries, achieving substantial accuracy gains even in the most challenging decision-making scenarios.
ScaffoldAgent's utility-guided approach ensures that outlines evolve dynamically, leading to superior long-form report generation and improved factual accuracy.
LLMs can reason far better on clinical records when demonstrations are selected using a graph-guided approach that combines patient data with LLM-estimated information gain.
