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cs.CV2025
Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark
Ziming Cheng, Binrui Xu, Lisheng Gong +14
With enhanced capabilities and widespread applications, Multimodal Large Language Models (MLLMs) are increasingly required to process and reason over multiple images simultaneously…
cs.CV2022
Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval
Siyu Ren, Kenny Q. Zhu
Current text-image approaches (e.g., CLIP) typically adopt dual-encoder architecture using pre-trained vision-language representation. However, these models still pose non-trivial…