6 citations · 9 across the 4 of their papers we have counts for
4 papers
On the Origins of Linear Representations in Large Language Models
Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar +2
Recent works have argued that high-level semantic concepts are encoded "linearly" in the representation space of large language models. In this work, we study the origins of such l…
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
Jacy Reese Anthis, Victor Veitch
Counterfactual fairness requires that a person would have been classified in the same way by an AI or other algorithmic system if they had a different protected class, such as a di…
Uncovering Meanings of Embeddings via Partial Orthogonality
Yibo Jiang, Bryon Aragam, Victor Veitch
Machine learning tools often rely on embedding text as vectors of real numbers. In this paper, we study how the semantic structure of language is encoded in the algebraic structure…
Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang, Victor Veitch
Real-world classification problems must contend with domain shift, the (potential) mismatch between the domain where a model is deployed and the domain(s) where the training data w…