Transformers are Universal In-context Learners

2 August 2024

Papers citing "Transformers are Universal In-context Learners"

6 / 6 papers shown

Title
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 56 0 0 03 Mar 2025
Towards Understanding the Universality of Transformers for Next-Token Prediction Michael E. Sander Gabriel Peyré CML 29 0 0 03 Oct 2024
How do Transformers perform In-Context Autoregressive Learning? Michael E. Sander Raja Giryes Taiji Suzuki Mathieu Blondel Gabriel Peyré 16 7 0 08 Feb 2024
Small Transformers Compute Universal Metric Embeddings Anastasis Kratsios Valentin Debarnot Ivan Dokmanić 52 11 0 14 Sep 2022
Your Transformer May Not be as Powerful as You Expect Shengjie Luo Shanda Li Shuxin Zheng Tie-Yan Liu Liwei Wang Di He 52 50 0 26 May 2022
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 219 13,886 0 02 Dec 2016