8 papers
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…
CARES: Context-Aware Resolution Selector for VLMs
Moshe Kimhi, Nimrod Shabtay, Raja Giryes +2
Large vision-language models (VLMs) commonly process images at native or high resolution to remain effective across tasks. This inflates visual tokens ofter to 97-99% of total toke…
Overflow Prevention Enhances Long-Context Recurrent LLMs
Assaf Ben-Kish, Itamar Zimerman, M. Jehanzeb Mirza +4
A recent trend in LLMs is developing recurrent sub-quadratic models that improve long-context processing efficiency. We investigate leading large long-context models, focusing on h…
LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content
Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh +9
The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required world knowledge to perform effe…
Teaching VLMs to Localize Specific Objects from In-context Examples
Sivan Doveh, Nimrod Shabtay, Wei Lin +9
Vision-Language Models (VLMs) have shown remarkable capabilities across diverse visual tasks, including image recognition, video understanding, and Visual Question Answering (VQA)…
Deep Phase Coded Image Prior
Nimrod Shabtay, Eli Schwartz, Raja Giryes
Phase-coded imaging is a computational imaging method designed to tackle tasks such as passive depth estimation and extended depth of field (EDOF) using depth cues inserted during…