# Perceive to Hypothesize, Verify to Ground: An Agentic Reasoning Framework for Open-World Geo-Localization

arXiv: https://arxiv.org/abs/2608.29880 · HTML: https://mlsanity.com/paper/2608.29880/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning.
- Builds on 26 of its 46 references that are in the map.
- First posted on arXiv 30 Aug 2026.

## Placed in

- LLM reasoning / [Spatial and embodied reasoning](https://mlsanity.com/lr/spatial-and-embodied-reasoning/)
- LLM agents and tool use / [Multimodal and embodied agents](https://mlsanity.com/agents/multimodal-and-embodied-agents/)

## Builds on (most cited first, 26 of 26)

- [WebResearcher: Unleashing unbounded reasoning capability in Long-Horizon Agents](https://mlsanity.com/paper/2509.13309/) (2025)
- [Scaling Test-time Compute for LLM Agents](https://mlsanity.com/paper/2506.12928/) (2025)
- [Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets](https://mlsanity.com/paper/2604.02460/) (2026)
- [Recognition through Reasoning: Reinforcing Image Geo-localization with Large Vision-Language Models](https://mlsanity.com/paper/2506.14674/) (2025)
- [GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model](https://mlsanity.com/paper/2406.18572/) (2024)
- [GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains](https://mlsanity.com/paper/2505.18700/) (2025)
- [Learn the Ropes, Then Trust the Wins: Self-imitation with Progressive Exploration for Agentic Reinforcement Learning](https://mlsanity.com/paper/2509.22601/) (2025)
- [GeoVista: Web-Augmented Agentic Visual Reasoning for Geolocalization](https://mlsanity.com/paper/2511.15705/) (2025)
- [Thinking with Map: Reinforced Parallel Map-Augmented Agent for Geolocalization](https://mlsanity.com/paper/2601.05432/) (2026)
- [GeoToken: Hierarchical Geolocalization of Images via Next Token Prediction](https://mlsanity.com/paper/2511.01082/) (2025)
- [SpotAgent: Grounding Visual Geo-localization in Large Vision-Language Models through Agentic Reasoning](https://mlsanity.com/paper/2602.09463/) (2026)
- [GraphGeo: Multi-Agent Debate Framework for Visual Geo-localization with Heterogeneous Graph Neural Networks](https://mlsanity.com/paper/2511.00908/) (2025)
- [GAEA: A Geolocation Aware Conversational Assistant](https://mlsanity.com/paper/2503.16423/) (2025)
- [GeoArena: Evaluating Open-World Geographic Reasoning in Large Vision-Language Models](https://mlsanity.com/paper/2509.04334/) (2025)
- [GeoRC: A Benchmark for Geolocation Reasoning Chains](https://mlsanity.com/paper/2601.21278/) (2026)
- [GeoExplain: Multimodal Reasoning based on Hierarchy of Visual Information in Street View](https://mlsanity.com/paper/2506.16633/) (2025)
- [MATA: A Trainable Hierarchical Automaton System for Multi-Agent Visual Reasoning](https://mlsanity.com/paper/2601.19204/) (2026)
- [GeoBrowse: A Geolocation Benchmark for Agentic Tool Use with Expert-Annotated Reasoning Traces](https://mlsanity.com/paper/2604.04017/) (2026)
- [Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory](https://mlsanity.com/paper/2605.24602/) (2026)
- [Reasoning or Pattern Matching? Probing Large Vision-Language Models with Visual Puzzles](https://mlsanity.com/paper/2601.13705/) (2026)
- [VisTIRA: Closing the Image-Text Modality Gap in Visual Math Reasoning via Structured Tool Integration](https://mlsanity.com/paper/2601.14440/) (2026)
- [Locatability-Guided Adaptive Reasoning for Image Geo-Localization with Vision-Language Models](https://mlsanity.com/paper/2603.13628/) (2026)
- [Thinking in Text and Images: Interleaved Vision--Language Reasoning Traces for Long-Horizon Robot Manipulation](https://mlsanity.com/paper/2605.00438/) (2026)
- [Geospatial Representation Learning: A Survey from Deep Learning to The LLM Era](https://mlsanity.com/paper/2505.09651/) (2025)
- [Skill-Conditioned Visual Geolocation for Vision-Language Models](https://mlsanity.com/paper/2604.09025/) (2026)
- [CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment](https://mlsanity.com/paper/2608.21041/) (2026)

## Abstract (arXiv)

Open-world geo-localization requires models to reason over ambiguous visual cues through multi-step reasoning and external knowledge grounding. While recent large vision-language models exhibit strong multimodal reasoning capabilities, existing approaches still suffer from perceptual hallucination and context drift due to the lack of explicit evidence-grounded verification. In this work, we reformulate geo-localization as a human-like perceive-then-verify reasoning problem and propose GeoPAVE (Geo-localization Perception-and-Verification-Engine), a bi-level agentic framework that contains perception-based hypothesis generation via single-pass rollouts and verification-based evidence grounding for decision actions: support, refute, and refine. To support rigorous evaluation, we further introduce PAVED, a novel dataset derived from real-world user check-in data, equipped with comprehensive reasoning trajectories featuring multi-hop queries, multi-round tool invocations, and structured perception-verification traces. The dataset and code are available at https://github.com/Arandinglv/GeoPAVE.