2026· International Conference on Conceptual Structures· pp. 473-487· 0 citations· 22 references
Computer Science
TL;DR
This study presents an exploration of an alternative approach in which LLMs serve as external assistants rather than as agents within simulations, called XABM (eX-plainable Generative ABM), which aims to make computational modeling more interpretable and reproducible.
VISA is presented, a structured, symbol-based description protocol that specifies a model in eight interconnected tables---four at the agent level (Agent, Variable, Sensing, Internal Function) and four at the model level (Associated Data, Input/Output, Schedule, Validation)---under the principle of minimality with comp...
Overall, the results show that SAE- and probe-based techniques often outperform basic prompt-based methods for steering LLM agents, although this advantage depends on the specific prompting strategy involved.
Jia-Run Fan, Arul Murugan, Shreyas R. Krishnan et al.· 0 citations
This article introduces a framework for designing and running simulated experiments with LLM‐powered agents and applies the framework to the exploration–exploitation dilemma and shows that LLM‐based experiments reproduce patterns observed among human participants.
Experiments reveal that models with similar end-to-end accuracy can exhibit markedly different agentic capability profiles, demonstrating that process-level evaluation is crucial for interpreting the true potential of LLMs and guiding the development of next-generation mathematical agents.
Jiayi Kuang, Ying-Hui Li, Yun-Ze Song et al.· 0 citations
Rosetta is presented, a multi-agent LLM pipeline that automatically generates first-principles analytical models from research paper PDFs, and four design decisions address failure modes of na\"ive LLM-based generation.
An environment-grounded audit is introduced in which every intermediate proposal receives an exact outcome in an evolutionary Contexto search whose feedback function assigns every valid guess an exact rank without human annotation.
En-Rong Pan, Ryan Zhou, Ting Hu· Inquiry@Queen's Undergraduat...· 0 citations
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