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README.md
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---
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configs:
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- config_name: anchor_recognition
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data_files:
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- split: test
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path: anchor_recognition/test-00000.parquet
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- config_name: cognitive_mapping
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data_files:
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- split: test
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path: cognitive_mapping/test-00000.parquet
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- config_name: global_counting
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data_files:
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- split: test
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path: global_counting/test-00000.parquet
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- config_name: relative_direction
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data_files:
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- split: test
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path: relative_direction/test-00000.parquet
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- config_name: relative_distance
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data_files:
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- split: test
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path: relative_distance/test-00000.parquet
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---
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# COSMIC
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GitHub: [https://github.com/ankursikarwar/Cosmic](https://github.com/ankursikarwar/Cosmic)
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Overview
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Humans routinely transform local, viewpoint-dependent observations into shared spatial models through language. COSMIC asks whether MLLMs can do the same. The benchmark places two static agents in the same indoor scene from different egocentric viewpoints. The agents must communicate exclusively through natural language to jointly solve a spatial QA task.
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## Citation
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```bibtex
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@misc{sikarwar2026communicatingspacelanguagemediatedspatial,
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title={Communicating about Space: Language-Mediated Spatial Integration Across Partial Views},
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author={Ankur Sikarwar and Debangan Mishra and Sudarshan Nikhil and Ponnurangam Kumaraguru and Aishwarya Agrawal},
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year={2026},
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eprint={2603.27183},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2603.27183},
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}
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```
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## Usage
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```python
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from datasets import load_dataset
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ds_anchor_recognition = load_dataset("mair-lab/Cosmic", name="anchor_recognition", split="test")
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ds_cognitive_mapping = load_dataset("mair-lab/Cosmic", name="cognitive_mapping", split="test")
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ds_global_counting = load_dataset("mair-lab/Cosmic", name="global_counting", split="test")
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ds_relative_direction = load_dataset("mair-lab/Cosmic", name="relative_direction", split="test")
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ds_relative_distance = load_dataset("mair-lab/Cosmic", name="relative_distance", split="test")
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```
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