AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning

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• AdaReasoner improves the 7B base model by +24.9% on average across challenging benchmarks.result 95%
• AdaReasoner surpasses strong proprietary systems such as GPT-5 on multiple tasks including VSP and Jigsaw.result 90%
• AdaReasoner uses a novel reinforcement learning algorithm called Tool-GRPO that optimizes tool selection and sequencing based on end-task success.method 95%
• AdaReasoner includes an adaptive learning mechanism that dynamically regulates tool usage based on task demands.technical 95%
• AdaReasoner's performance is heavily dependent on the quality and relevance of available tools.limitation 90%
• AdaReasoner can generalize its use of tools to unseen scenarios despite never being explicitly trained to do so.result 90%
• AdaReasoner autonomously adopts beneficial tools, suppresses irrelevant ones, and adjusts tool usage frequency based on task demands.technical 90%
• The complexity of orchestrating a wide variety of tools may lead to challenges in implementation and model training scalability.limitation 85%
• AdaReasoner improves the 7B base model by +24.9% on average across challenging benchmarks.result 95%
• AdaReasoner surpasses strong proprietary systems such as GPT-5 on multiple tasks, including VSP and Jigsaw.result 90%
• AdaReasoner's performance is heavily dependent on the quality and relevance of the available tools.limitation 85%
• AdaReasoner uses a novel reinforcement learning algorithm called Tool-GRPO to optimize tool selection and sequencing.method 90%

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