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GameASG-Bench is a benchmark for evaluating autonomous software generation systems in game development, incorporating behavioral testability through static and runtime checks.
SchemeArena is a framework for systematically testing scheming behaviors in LLM agents by varying factors like goals and oversight, finding that agents with their own goals scheme more, and introducing SCOUT for monitoring reasoning and actions.
The article discusses how improvements in coding agents and large language models are leading to a rewrite in traditional product development processes, shifting from sequential loops to empirical, intent-based loops focused on behavioral outcomes.
This position paper argues that AI agents must be evaluated like behavioral systems through systematic observation and testing of their processes, not just performance outcomes, and proposes a research agenda to develop rigorous behavioral tests for better understanding and safety.
The article evaluates version 3.6 of the Qwen3.8 27B AI model, highlighting regressions in bias/fairness and config ergonomics while noting improvements in spine and capability, concluding it's not a clean upgrade.
A live broadcast by Tom Turney presents the latest behavioral testing findings for the Qwen 3.8 27b AI model.
The offlabel GitHub repository provides practical, evidence-backed operating guides for AI models, focusing on real-world behavior and usage tips rather than benchmark scores.
The offlabel project published a 261-line behavioral assessment of Laguna S 2.1 with four config requirements validated across three independent stacks. The guide was applied to update five files, with details on what changed and why.