Krunoslav Lehman Pavasovic
@KrunoLehman
PhD in Generative AI @Meta & @ENS_ULM. Previously at @Inria, @ETH, @UniOfOxford, @CERN.
We present an Autoregressive U-Net that incorporates tokenization inside the model, pooling raw bytes into words then word-groups. AU-Net focuses most of its compute on building latent vectors that correspond to larger units of meaning. Joint work with @byoubii 1/8
DINOv2 meets text at #CVPR 2025! Why choose between high-quality DINO features and CLIP-style vision-language alignment? Pick both with dino.txt ๐ฆ๐ We align frozen DINOv2 features with text captions, obtaining both image-level and patch-level alignment at a minimal cost. [1/N]
๐จ Your RL only improves ๐ฝ๐ฎ๐๐@๐ญ, not ๐ฝ๐ฎ๐๐@๐ธ? ๐จ Thatโs not a bug โ itโs a ๐ณ๐ฒ๐ฎ๐๐๐ฟ๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ผ๐ฏ๐ท๐ฒ๐ฐ๐๐ถ๐๐ฒ youโre optimizing. You get what you optimize for. If you want better pass@k, you need to optimize for pass@k at training time. ๐งต How?
๐ท Hello Singapore! Meta is at #ICLR2025 EXPO ๐ท Meta will be in Singapore this week for #ICLR25! Stop by our booth to chat with our team or learn more about our latest research. Things to know: ๐ท Find us @ Booth #L03 (Rows 3-4, Columns L-M) in Hall 2. ๐ท We're sharing 50+โฆ
Neat paper on classifier-free guidance by K. Pavasovic, J. Verbeek, @GiulioBiroli & M. Mezard: arxiv.org/abs/2502.07849โฆ