The Challenge of Compositionality for Artificial Intelligence
Online · 2022
Organized by Raphaël Millière & Gary Marcus
Official website
Recordings
Day 1: Why Compositionality Matters for AI
- Gary Marcus – "Compositionality and Natural Language Understanding"
- Allyson Ettinger – "Shades of Meaning Composition: Defining Compositionality Goals in NLU"
- Paul Smolensky – "Human-Level Intelligence Requires Continuous, Robustly Compositional Representations: Neurocompositional Computing for NECST-Generation AI"
- Raphaël Millière – "Compositionality Without Constituency"
Day 2: Can Language Models Handle Compositionality?
- Dieuwke Hupkes – "Are Neural Networks Compositional, and How Do We Even Know?"
- Tal Linzen – "Successes and Failures of Compositionality in Neural Networks for Language"
- Stephanie Chan – "Data Distributions Drive Emergent In-Context Learning in Transformers"
- Ellie Pavlick – "No One Metric is Enough! Combining Evaluation Techniques to Uncover Latent Structure"
- Brenden Lake – "Human-Like Compositional Generalization Through Meta-Learning"
Speakers