Papers by Liaoni Wu

1 papers
Thinking with Map: Reinforced Parallel Map-Augmented Agent for Geolocalization (2026.findings-acl)

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Challenge: Existing large vision-language model (LVLM) approaches overlook a common strategy used by humans — using maps.
Approach: They propose a method to equip a vision-language model with the ability to think with maps and optimize it using agentic reinforcement learning and parallel test-time scaling.
Outcome: The proposed method outperforms open- and closed-source models on most metrics.

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