11
Jan
©geralt - pixabay.com
Linear Structure of High-Level Concepts in Text-Controlled Generative Models
Victor Veitch, University of Chicago
11.01.2024
5:15 pm - 6:45 pm
LMU Institute of AI in Management via zoom
Text controlled generative models (such as large language models or text-to-image diffusion models) operate by embedding natural language into a vector representation, then using this representation to sample from the model’s output space. This talk concerns how high-level semantics are encoded in the algebraic structure of representations.
Related
©jittawit.21 - stock.adobe.com
AI Keynote Series • 08.08.2024 • Online via Zoom
tba
Join the lecture with Michael Oberst from Johns Hopkins University.
©jittawit.21 - stock.adobe.com
AI Keynote Series • 18.07.2024 • Online via Zoom
Representation Learning: A Causal Perspective
Lecture with Yixin Wang from University of Michigan, applying causal insights to create clear, efficient representations using counterfactuals.
©jittawit.21 - stock.adobe.com
AI Keynote Series • 06.06.2024 • Online via Zoom
Interpretable prediction with missing values
Missing values in healthcare data hinder interpretability and predictions. Fredrik Johansson's talk presents two solutions and suggests future research directions.
©jittawit.21 - stock.adobe.com
AI Keynote Series • 23.05.2024 • Online via Zoom
Innovating AI Products for Social Good in the Age of Foundational Models
Professor Qian Yang explores how LLMs necessitate considering societal impacts and innovating for social good in education and mental healthcare.
©geralt - pixabay.com
AI Keynote Series • 08.02.2024 • LMU Institute of AI in Management via zoom
Causal Scoring: A Framework for Effect Estimation, Effect Ordering, and Effect Classification
The presentation introduces causal scoring for decision-making, with interpretations.