Or Patashnik

Localization signals in VLMs remain hidden in intermediate representations, leading to significant failures in current image editing pipelines.

Semantic Browsing transforms image generation by allowing users to explore diverse visual interpretations through structured, meaningful variations rather than random noise.

Achieving a 4x speedup in multi-reference image generation without sacrificing visual quality by intelligently dropping reference tokens.

ScenA reveals that conditioning on free-form prompts and reference voices can produce more authentic multi-speaker audio scenes than traditional structured methods.