7 citations · 8 across the 8 of their papers we have counts for
3 papers · 1 filter
Balanced Thinking: Improving Chain of Thought Training in Vision Language Models
Shaked Perek, Ben Wiesel, Avihu Dekel +2
Multimodal reasoning in vision-language models (VLMs) typically relies on a two-stage process: supervised fine-tuning (SFT) and reinforcement learning (RL). In standard SFT, all to…
Look Where It Matters: High-Resolution Crops Retrieval for Efficient VLMs
Nimrod Shabtay, Moshe Kimhi, Artem Spector +5
Vision-language models (VLMs) typically process images at a native high-resolution, forcing a trade-off between accuracy and computational efficiency: high-resolution inputs captur…
CLIMP: Contrastive Language-Image Mamba Pretraining
Nimrod Shabtay, Itamar Zimerman, Eli Schwartz +1
Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and scales quadratically with resolu…