Papers by Utkarsh Mishra

1 papers
Can MLLMs Find Their Way in a City? Exploring Emergent Navigation from Web-Scale Knowledge (2026.eacl-long)

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Challenge: Existing evaluation benchmarks for multimodal large language models (MLLMs) are language-centric or heavily reliant on simulated environments, rarely probing the nuanced, knowledge-intensive reasoning essential for practical, real-world scenarios.
Approach: They propose a task of Sparsely Grounded Visual Navigation to evaluate MLLM-driven agents in city navigation in four diverse global cities.
Outcome: The proposed benchmark encompassing four diverse global cities evaluates agents' decision-making abilities in city navigation.

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