Evidence Alignment and Transfer Boundaries in Llm Social Agents And Multimodal Executive Agents

Abstract

Progress in LLM social agents and multimodal executive agents depends on more than accumulating favorable results. This critical synthesis connects a realistic benchmark centered on persistent LLM-based social-media agents with a paired text-only and multimodal benchmark for constrained executive decision tasks and asks how measurement choices, boundary conditions, and decision costs shape the interpretation of both. A structured reading of two target studies and 12 verified companion references is conducted across five lenses: behavioral realism, memory, interaction effects, safety, benchmark validity. Emphasis is placed on the provenance of evidence, the comparability of baselines, and the consequences of alternative explanations. The combined literature indicates that methodological gains become actionable only when behavioral realism and memory are evaluated together and when limits associated with benchmark validity are explicit. This shifts the emphasis from isolated scores toward traceable chains of evidence and decision relevance. The article concludes with a research agenda built around transparent comparators, targeted stress tests, and evidence records that can be reused without overstating causal or practical reach.