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LLM-Agent Stress Test: Feed Effects on Lexical Diversity
US & West ·
A peer-voted social-platform testbed PV-SST is introduced to study population-level behavior of LLM agents. In a preregistered experiment with 448 trials, a feed of previous posts ranked by likes increased final-round lexical similarity, but no reliable advantage for distributed sources was found.
Why it matters
This work is important for understanding collective agent behavior and how social mechanisms can affect simulation outcomes.
arXiv:2610.29559v1 Announce Type: new Abstract: Model predictive control is a high-performance control method, but it incurs comparatively high online computational costs across many control tasks and is challenging to realize in low-level hardware settings.
arXiv:2610.29377v1 Announce Type: cross Abstract: Learning-based path planners based on diffusion and flow matching can generate diverse trajectories from demonstrations but typically lack mechanisms for constraint satisfaction and collision avoidance during deployment.
arXiv:2604.04455v3 Announce Type: replace Abstract: Nonlinear underactuated systems such as two-wheeled inverted pendulums (TWIPs) exhibit a limited region of attraction (RoA), which defines the set of initial conditions from which the closed-loop system converges to the equilibrium.
