Papers with spatial awareness
LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression (2025.findings-naacl)
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Souvik Kundu, Anahita Bhiwandiwalla, Sungduk Yu, Phillip Howard, Tiep Le, Sharath Nittur Sridhar, David Cobbley, Hao Kang, Vasudev Lal
| Challenge: | LVLMs have been shown to perform well on simple uni-modal benchmarks, but their detailed study on multi-modal models is still lacking. |
| Approach: | They propose a framework to analyze the impact of compression on LVLMs on multi-modal input driven tasks. |
| Outcome: | The proposed framework analyzes the impact of compression on generative performance of large vision language models on multi-modal input driven tasks. |
iVISPAR — An Interactive Visual-Spatial Reasoning Benchmark for VLMs (2025.emnlp-main)
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| Challenge: | Vision-Language Models (VLMs) struggle with spatial reasoning and visual alignment, despite their performance on 2D tasks. |
| Approach: | They propose a multimodal benchmark to evaluate VLMs' spatial reasoning capabilities based on the sliding tile puzzle . |
| Outcome: | The proposed model performs better on 2D tasks compared to 3D or text-based settings, but struggles with complex spatial configurations and consistently falls short of human performance. |