5 results for "safety performance"
Discovering Agentic Safety Specifications from 1-Bit Danger Signals
Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for Safe Agents), a framework where an LLM iterative…
Quantifying Divergence in Inter-LLM Communication Through API Retrieval and Ranking
Large language models (LLMs) increasingly operate as autonomous agents that reason over external APIs to perform complex tasks. However, their reliability and agreement remain poorly characterized. We…
An Information-Geometric Framework for Stability Analysis of Large Language Models under Entropic Stress
As large language models (LLMs) are increasingly deployed in high-stakes and operational settings, evaluation strategies based solely on aggregate accuracy are often insucient to characterize system r…
The Kerimov-Alekberli Model: An Information-Geometric Framework for Real-Time System Stability
This study introduces the Kerimov-Alekberli model, a novel information-geometric framework that redefines AI safety by formally linking non-equilibrium thermodynamics to stochastic control for the eth…
The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications
Given the increased use of LLMs in financial systems today, it becomes important to evaluate the safety and robustness of such systems. One failure mode that LLMs frequently display in general domain …