Hugging Face Trending Papers August 4, 2026

Geo-Embed: Towards Unified Multimodal Embeddings for Urban Understanding

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Geospatial and urban applications increasingly require models to compare heterogeneous evidence across street-view imagery, remote-sensing observations, text descriptions, region proposals, and temporal change cues. However, existing multimodal embedding models and benchmarks are still largely designed and evaluated around general-purpose image-text matching, leaving unclear whether unified embedding space can support heterogeneous geospatial tasks involving spatial relationships, fine-grained semantics, and temporal changes.

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arXiv Machine Learning

Aug 5

Geo-Embed: Towards Unified Multimodal Embeddings for Urban Understanding

arXiv:2608. 03826v1 Announce Type: cross Abstract: Geospatial and urban applications increasingly require models to compare heterogeneous evidence across street-view imagery, remote-sensing observations, text descriptions, region proposals, and temporal change cues.

By Jiapeng Li, Yong Li, Junjie Zhou, Fan Zhang, Yu Liu

rag nlp multimodal benchmarks

arXiv Computer Vision

Sep 24

VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing

The paper introduces RSMEB, a unified benchmark for remote‑sensing multimodal retrieval that evaluates both cross‑modal and interleaved retrieval across 21 tasks under a single ranking protocol. It also presents VLM2GeoVec, an instruction‑conditioned single‑encoder model that embeds image, text, bounding‑box, and geo‑coordinate tokens into one sequence and achieves state‑of‑the‑art performance on region‑caption, referring‑expression, and semantic geo‑aware retrieval while remaining competitive on conventional tasks. The authors provide code, checkpoints, and data on GitHub to facilitate reproducibility.

By Emanuel S\'anchez Aimar, Gulnaz Zhambulova, Fahad Shahbaz Khan, Yonghao Xu, Michael Felsberg

rag multimodal benchmarks

arXiv Computer Vision

Sep 23

GeoBridge++: Fact-Guided Geo-Semantic Bridging for Unified Cross-View Geo-Localization

arXiv:2512.02697v4 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images matching a query image. However, the traditional satellite-...

By Zixuan Song, Jing Zhang, Di Wang, Zhiming Luo, Wenbin Liu, Haonan Guo, En Wang, Bo Du, Liangpei Zhang

robotics multimodal benchmarks

arXiv Machine Learning

Sep 22

MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments

arXiv:2505.12254v3 Announce Type: replace-cross Abstract: Existing visual place recognition (VPR) datasets predominantly rely on vehicle-mounted imagery, offer limited multimodal diversity, and under...

By Yiwei Ou, Xiaobin Ren, Ronggui Sun, Guansong Gao, Kaiqi Zhao, Manfredo Manfredini

llms multimodal benchmarks

arXiv AI

Jul 21

LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models

arXiv:2607. 16305v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong progress in multimodal understanding.

By Zeyu Xu, Xingzhong Hou, Pengkai Guo, Siling Lin, Xiao Xu, Menghua Zhai, Haoyu Chen, Yunke Zhang, Fei Huang

llms rag multimodal benchmarks

arXiv Machine Learning

Sep 1

SynMulti: Synthetic-to-Real Learning for Multimodal Video Understanding

arXiv:2604.12335v2 Announce Type: replace-cross Abstract: Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as...

By Tanzila Rahman, Renjie Liao, Leonid Sigal

llms computer-vision nlp fine-tuning multimodal

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Geo-Embed: Towards Unified Multimodal Embeddings for Urban Understanding

VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing

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