AMIGO: Agentic Multi-Image Grounding Oracle Benchmark
📰 ArXiv cs.AI
AMIGO is a benchmark for evaluating agentic vision-language models on long-horizon tasks with multiple images
Action Steps
- Design a benchmark with a long-horizon task that requires the model to identify a target image from a gallery of visually similar images
- Implement a sequence of attribute-focused questions to recover the target image
- Evaluate the model's performance using metrics such as accuracy and efficiency
- Compare the results with other models and analyze the strengths and weaknesses of each model
Who Needs to Know This
AI researchers and engineers working on vision-language models can benefit from AMIGO to evaluate their models' performance on complex tasks, and product managers can use it to assess the capabilities of AI models in real-world applications
Key Insight
💡 AMIGO provides a challenging testbed for evaluating the capabilities of agentic vision-language models in real-world applications
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📸 Introducing AMIGO, a benchmark for evaluating agentic vision-language models on long-horizon tasks with multiple images!
Key Takeaways
AMIGO is a benchmark for evaluating agentic vision-language models on long-horizon tasks with multiple images
Full Article
Title: AMIGO: Agentic Multi-Image Grounding Oracle Benchmark
Abstract:
arXiv:2603.28662v1 Announce Type: cross Abstract: Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn correctness. We introduce AMIGO (Agentic Multi-Image Grounding Oracle Benchmark), a long-horizon benchmark for hidden-target identification over galleries of visually similar images. In AMIGO, the oracle privately selects a target image, and the model must recover it by asking a sequence of attribute-focused
Abstract:
arXiv:2603.28662v1 Announce Type: cross Abstract: Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn correctness. We introduce AMIGO (Agentic Multi-Image Grounding Oracle Benchmark), a long-horizon benchmark for hidden-target identification over galleries of visually similar images. In AMIGO, the oracle privately selects a target image, and the model must recover it by asking a sequence of attribute-focused
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