6 citations · 11 across the 15 of their papers we have counts for
5 papers · 1 filter
The Universal Weight Subspace Hypothesis
Prakhar Kaushik, Shravan Chaudhari, Ankit Vaidya +2
We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence…
Perceptual Taxonomy: Evaluating and Guiding Hierarchical Scene Reasoning in Vision-Language Models
Jonathan Lee, Xingrui Wang, Jiawei Peng +9
We propose Perceptual Taxonomy, a structured process of scene understanding that first recognizes objects and their spatial configurations, then infers task-relevant properties suc…
TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing
Eddie Pokming Sheung, Qihao Liu, Wufei Ma +3
With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in…
Progressive Prompt Detailing for Improved Alignment in Text-to-Image Generative Models
Ketan Suhaas Saichandran, Xavier Thomas, Prakhar Kaushik +1
Text-to-image generative models often struggle with long prompts detailing complex scenes, diverse objects with distinct visual characteristics and spatial relationships. In this w…
EigenLoRAx: Recycling Adapters to Find Principal Subspaces for Resource-Efficient Adaptation and Inference
Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +1
The rapid growth of large models has raised concerns about their environmental impact and equity in accessibility due to significant computational costs. Low-Rank Adapters (LoRA) o…