Topic
deliberation
Hidden Anchors Reveal Why Multi-Agent LLM Deliberation Escapes Groupthink
A new paper from arXiv models multi-agent LLM deliberation as a closed-loop dynamical system where each agent has a hidden internal belief, or anchor, that continually pulls its opinion. The model explains how agents' confidence can climb past where any agent started, escaping the convex hull of initial beliefs. Tests across three open-weight model families show the anchor's influence is a spectrum.
PACT Hybrid Architecture Combines Small Language Model Planning with Reinforcement Learning for Enhanced Decision-Making
Researchers propose Plan, Align, Commit, Think (PACT), a hybrid architecture that couples a fast reactive reinforcement learning policy with a slow deliberative small language model (SLM) planner. The SLM asynchronously generates and validates action plans, which are executed directly once verified as safe through simulation. Evaluated on three FrozenLake configurations, PACT outperformed all baselines using a 2B-parameter SLM backbone, demonstrating that deliberative planning and reactive execution complement each other.