2 citations · 4 across the 8 of their papers we have counts for
8 papers
Rethinking JEPA: Compute-Efficient Video SSL with Frozen Teachers
Xianhang Li, Chen Huang, Chun-Liang Li +4
Video Joint Embedding Predictive Architectures (V-JEPA) learn generalizable off-the-shelf video representation by predicting masked regions in latent space with an exponential movi…
How PARTs assemble into wholes: Learning the relative composition of images
Melika Ayoughi, Samira Abnar, Chen Huang +10
The composition of objects and their parts, along with object-object positional relationships, provides a rich source of information for representation learning. Hence, spatial-awa…
PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
Yu Meng, Kaiyuan Li, Chenran Huang +4
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a range of multimodal tasks. However, their inference efficiency is constrained by the large n…
Cavia: Camera-controllable Multi-view Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang +5
In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unso…
How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks
Etai Littwin, Omid Saremi, Madhu Advani +4
Two competing paradigms exist for self-supervised learning of data representations. Joint Embedding Predictive Architecture (JEPA) is a class of architectures in which semantically…
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization
Yuhang Zang, Hanlin Goh, Josh Susskind +1
Existing vision-language models exhibit strong generalization on a variety of visual domains and tasks. However, such models mainly perform zero-shot recognition in a closed-set ma…
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
Vimal Thilak, Chen Huang, Omid Saremi +5
Joint embedding (JE) architectures have emerged as a promising avenue for acquiring transferable data representations. A key obstacle to using JE methods, however, is the inherent…
Adaptivity and Modularity for Efficient Generalization Over Task Complexity
Samira Abnar, Omid Saremi, Laurent Dinh +8
Can transformers generalize efficiently on problems that require dealing with examples with different levels of difficulty? We introduce a new task tailored to assess generalizatio…