Vis-CoT: A Human-in-the-Loop Framework for Interactive Visualization and Intervention in LLM Chain-of-Thought Reasoning
Organizations: Department of Computer Science & Engineering University of Mauritius R´eduit 80837, Mauritius · Department of Electrical & Computer Engineering Cyprus University of Technology 3036 Limassol, Cyprus · Faculty of Electrical & Computer Engineering University of Prishtina ”Hasan Prishtina” 10000 Prishtina, Kosovo · Department of Computer Science University of Luxembourg L-4365 Esch-sur-Alzette, Luxembourg · Faculty of Computers, Informatics & Microelectronics Technical University of Moldova MD-2004 Chis¸in˘au, Moldova · Department of Computer Science University of Andorra AD600 Sant Juli`a de L`oria, Andorra · Department of Computer Science San Francisco State University San Francisco, CA 94132, India
Abstract
Large language models (LLMs) show strong reasoning via chain-of-thought (CoT) prompting, but the process is opaque, which makes verification, debugging, and control difficult in high-stakes settings. We present Vis-CoT, a human-in-the-loop framework that converts linear CoT text into an interactive reasoning graph. Users can visualize the logical flow, identify flawed steps, and intervene by pruning incorrect paths and grafting new, user-defined premises. This shifts interaction from passive observation to active collaboration, steering models toward more accurate and trustworthy conclusions. Across GSM8K and StrategyQA, Vis-CoT improves final-answer accuracy by up to 24 percentage points over non-interactive baselines. A user study also shows large gains in perceived usability and trust. Vis-CoT points to a practical path for more reliable, understandable, and collaborative reasoning by combining LLMs with targeted human oversight.