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Benchmarking the potential of large models as multi-modal search engines
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2026-03-09 14:25:24
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MMSearch: Benchmarking the potential of large models as multi-modal search engines More Research MathVerse ๐ฅ MathVista ๐ฅ LLaMA-Adapter (V2) ๐ฅ SPHINX-X ImageBind-LLM Point-Bind & Point-LLM PerSAM CoMat MMSearch Benchmarking the potential of large models as multi-modal search engines Dongzhi Jiang* 1 , Renrui Zhang*โ 1 , 2 , Ziyu Guo 3 , Yanmin Wu 5 , Jiayi Lei 4 , Pengshuo Qiu 4 , Pan Lu 6 , Zehui Chen 2 , Guanglu Song 7 , Peng Gao 4 , Yu Liu 7 , Chunyuan Li 2 , Hongsheng Li 1 1 CUHK MMLab, 2 ByteDance, 3 CUHK MiuLar Lab, 4 Shanghai AI Laboratory, 5 Peking University, 6 Stanford University, 7 Sensetime Research ICLR 2025 Paper arXiv Code ๐ค Dataset ๐ฎ Visualize ๐ Leaderboard Introduction The advent of Large Language Models (LLMs) has paved the way for AI search engines, e.g., SearchGPT, sh...
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