3 citations · 9 across the 13 of their papers we have counts for
6 papers · 1 filter
Meaning Representations from Trajectories in Autoregressive Models
Tian Yu Liu, Matthew Trager, Alessandro Achille +3
We propose to extract meaning representations from autoregressive language models by considering the distribution of all possible trajectories extending an input text. This strateg…
AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation
Yangchao Wu, Tian Yu Liu, Hyoungseob Park +3
Unsupervised depth completion and estimation methods are trained by minimizing reconstruction error. Block artifacts from resampling, intensity saturation, and occlusions are among…
Sub-token ViT Embedding via Stochastic Resonance Transformers
Dong Lao, Yangchao Wu, Tian Yu Liu +2
Vision Transformer (ViT) architectures represent images as collections of high-dimensional vectorized tokens, each corresponding to a rectangular non-overlapping patch. This repres…
Tangent Transformers for Composition, Privacy and Removal
Tian Yu Liu, Aditya Golatkar, Stefano Soatto
We introduce Tangent Attention Fine-Tuning (TAFT), a method for fine-tuning linearized transformers obtained by computing a First-order Taylor Expansion around a pre-trained initia…
Tangent Model Composition for Ensembling and Continual Fine-tuning
Tian Yu Liu, Stefano Soatto
Tangent Model Composition (TMC) is a method to combine component models independently fine-tuned around a pre-trained point. Component models are tangent vectors to the pre-trained…
Taming AI Bots: Controllability of Neural States in Large Language Models
Stefano Soatto, Paulo Tabuada, Pratik Chaudhari +1
We tackle the question of whether an agent can, by suitable choice of prompts, control an AI bot to any state. To that end, we first introduce a formal definition of ``meaning'' th…