EgoBench: An Interactive Egocentric Multimodal Benchmark for Tool-Using Agents

As AI agents increasingly operate in open, real-world environments, they require a deep synergy of multimodal perception, tool invocation with multi-hop reasoning, and dynamic interaction with users. However, existing benchmarks fail to jointly evaluate these capabilities due to challenges in designing strictly coupled multi-capability tasks, simulating natural and task-constrained user feedback, and ensuring objective evaluation of dynamic interaction. To bridge this gap, we introduce EgoBench,

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ethics.ai (27 May 2026), “EgoBench: An Interactive Egocentric Multimodal Benchmark for Tool-Using Agents,” evidence record 3635, https://ethics.ai/record/3635 (originally published by arXiv).

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