FIELD NOTES TOPIC
knowledge intensive tasks
2 notes, newest first.
Contextual Information Policy Optimization for Search Agents
The researchers propose a new reinforcement learning framework called Contextual Information Policy Optimization (CIPO) to improve the reliability of search agents for knowledge-intensive tasks. CIPO encourages the use…
From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search
Researchers propose Multi-Agent Protocol Distillation (MAPD), a method to bridge the gap between open-source and proprietary language models in solving knowledge-intensive tasks. MAPD uses a structured protocol as an…
